TW202340062A - Material handling system and method therefor - Google Patents

Abstract

A material handling system, for handling and placing packages onto pallets destined for an order store, including a storage array, an automated package transport system, an automated palletizer, and a controller operably connected to the automated palletizer, the controller being programmed with a pallet load generator with at least one pallet to order store affinity characteristic, for a predetermined method of pallet load packages distribution at the order store, the pallet load generator being configured so that a pallet load is formed by the automated palletizer of packages arranged in the pallet load embodying the at least one pallet to order store affinity characteristic.

Description

Material handling systems and methods

[Cross-reference to related applications]

This case claims the rights and interests of U.S. Provisional Patent Application No. 63/288,253 filed on December 10, 2021 and is a non-provisional patent application. The full text of the disclosure is incorporated herein by reference. [Field]

This disclosure relates generally to material handling systems and, more specifically, to the use of material handling systems to move and place cargo on pallets.

Warehouses or distribution centers for goods produce pallets of goods for various customers, where such customers include, but are not limited to, retail stores. An individual customer orders each of the goods, and the order is fulfilled by a warehouse or distribution center by loading the ordered goods onto one or more pallets. Each of the individual customers can have their own preferred way of depalletizing goods ordered from a warehouse or distribution center to facilitate the replenishment of those goods on store shelves.

According to one aspect of the present disclosure, a material handling system for handling and placing packages onto pallets destined for ordering stores includes: a storage array having storage space for receiving packages therein; an automated package transfer system communicatively connected to the storage array for storing packages in the storage space of the storage array and retrieving the packages from the storage space of the storage array; An automated stacker for placing packages onto pallets to form pallet loads, the automated stacker being communicatively connected to the automated package transfer system configured to transfer individual packages from the storage Arrays are provided to the automated stacker to form the pallet load, the pallet load including more than one composite layer package; and A controller operably connected to the automated stacker, the controller programmed to have a pallet load generator having at least one pallet pair ordering store affinity feature for use in the ordering A predetermined method of pallet load package distribution for a store, the pallet load generator configured such that the pallet load is formed by the automatic stacker placing the packages in the pallet load, embodying the at least one pallet pair ordering Store affinity features.

1 illustrates an example warehouse or distribution center 199 (generally referred to herein as warehouse 199) in accordance with aspects of the present disclosure. Although aspects of the present disclosure will be described with reference to the drawings, it should be understood that aspects of the present disclosure may be embodied in a variety of forms. Additionally, any suitable size, shape or type of elements or materials may be used.

Aspects of the present disclosure are generally applicable to warehouse systems in which pallet loads (such as those described herein and collectively referred to as pallet loads PALO) are established by automated machinery, such as robotic stackers 162, 162', based on controller generated Pallet plan. However, aspects of the present disclosure may also be applied to manual pallet creation, where the pallet load generator (as described herein) outputs an itemization of the container units CU to be included on the pallet (according to the present disclosure) , where human workers build pallets with predetermined itemized case units CU based on warehouse rules and previous work experience. Aspects of this disclosure may also be applied to manual warehouses where pallet plans are computer-generated and output in tangible forms (e.g., video monitors, graphical user interfaces, smart devices such as mobile phones and tablets, paper instructions, etc. ), for a human worker to follow in an advisory role to establish the pallet described here. Here, the goods contained in the pallet load PALO are delivered to human workers via conveyors, mobile robots or other suitable transport vehicles in a predetermined sequence inferred from the pallet plan.

In accordance with this disclosure, each pallet load PALO is planned using any suitable calculation method, including but not limited to U.S. Patent Nos. 8965559, issued on February 24, 2015, and 9969572, issued on May 15, 2018. The methods described in No. 1, the entire disclosure of which are incorporated herein by reference. As used herein, a "planned pallet" or "planned pallet load" is a unit with a cargo manifest (e.g., individual items, cases, totes, pallets, etc., as described herein, commonly referred to as case units CU). Pallet load, its distribution coordinates (X, Y, Z - see Figure 1) are used in the pallet coordinate system with coordinates close to the origin (X=0, Y=0, Z=0). The direction of the goods along the X, Y, and Z axes has values such as length, width, height, or width, length, height, etc. for goods that cannot be tilted. Can provide added value to goods that can be placed on surfaces on either side of the goods. These additional values include, for example, length, height, width, or width, height, length, or height, length, width, or height, width, length. A pallet plan is a physically valid scheme in which (1) the loads do not intersect in physical space, (2) each load is stably supported by other loads or the pallet base, and (3) no part of any load exceeds the pallet's external dimensions Lp, Wp, Hp (or the predetermined volume Vp of the pallet load defined by the external dimensions Lp, Wp, Hp), and (4) the total weight of the goods on the pallet does not exceed the predetermined pallet load PALO Maximum weight Wmax.

Also according to this disclosure, a "planned order" is a numbered list of planned pallets such that all ordered case units CU belong to some pallet in the list, and there are no case units CU that do not belong to any pallet load. It should be noted that consecutive case units CU in the order list do not have to be assigned to the same or consecutive pallet loads. For example, container unit number 1 can be assigned to pallet load number 5, while container unit number 2 can be assigned to pallet load number 3.

It should also be noted that the case unit CU can have an integer value of the "product group type" to which the case unit CU in the retail store belongs. For example, retail stores typically assign predetermined relationships between these product group types and the physical locations within the store (eg, aisles, departments, areas, etc.) where the product group types are located. As used in this article, the types of product groups and corresponding physical locations within a retail store are often referred to as "aisles." It should be noted that the aisles are those within a retail store and should not be confused with the (distribution center) storage/picking aisles of the storage array 130 of the (distribution center) material handling system 190 . Here, the retail store aisles and distribution center picking aisles (storage array 130) are completely separated from each other. It should also be noted that retail store aisles are numbered from 1 to n (e.g., aisle 1, aisle 2, ..., aisle n), where n is an integer value representing the predetermined highest aisle number for a given store. Although aisles may be numbered, the location of the aisles in the store may not be contiguous. In accordance with aspects of the present disclosure, case units CU belonging to a common (eg, the same) aisle (eg, physical location/aisle and/or product group type) are assigned to the pallet load package allocation method described herein. Common pallet (unless otherwise stated).

In one aspect, a close number of aisles in a retail store (eg, such as aisles 34 and 35) may be physically close to each other in space. In this aspect, the present disclosure may optimize products placed on a given pallet by grouping products from physically proximate aisles (e.g., aisles 34 and 35) on a common pallet rather than Combine products from aisles that are physically separate from each other (eg, aisles 34 and 73).

In other aspects, the relationship between aisle numbers and spatial proximity of aisles may be more complex than the physical proximity of adjacent aisle numbers (eg, aisles 34 and 35) in space. For example, adjacent or close aisle numbers (e.g., aisle 20 and aisle 21) may not mean that the aisles are physically close to each other in space (e.g., aisle 20 may be located at one end of a retail store, while aisle 21 may be located at the retail store). other end of the store). Here, for allocating tote units to pallet loads, a pairwise relationship between two aisles can be provided, as described in this article. For example, according to aspects of the present disclosure, a pairwise relationship between two aisles exists in the form of coefficients A[i,k] for aisle i and aisle k. This pairwise relationship describes not only the physical proximity between two aisles, but also the retail store's preference to keep products in those aisles on one pallet or on separate pallets based on, e.g., distance Offloading retail store business logic outside of optimization. An example of such business logic could be the separation of alkaline products (eg, laundry detergent) and food products (eg, baby food), which are preferably transported on separate pallet loads.

Aspects of this disclosure also apply to any suitable volume of product in any given aisle. For example, the total container unit volume of some aisles may be much larger than the volume of a single pallet (see, for example, volume V2 of aisle 2 in Figure 5). Here, aspects of the present disclosure allocate the volume of the container unit to the entire pallet load until the remaining volume of the container unit does not fill the entire pallet load. Here, the remaining volume of case units is allocated to pallets according to the parcel allocation method described here. As another example, the volume of tote units for other aisles may be several tote units or even a single tote unit, in which case these tote units are allocated to pallets according to the packaging allocation method described herein. board load.

Referring also to Figures 2-4, as will be described herein, the material handling system 190 of the warehouse 199 is configured to optimize the automated process (see, eg, Figure 2) of planning and establishing mixed product orders 299 that are to be delivered to For example, a retail store (or other suitable customer who delivers the goods to the pallet). The retail store where the order is placed is referred to herein as ordering store 200 (see, eg, Figures 2-4). Each of the one or more pallets loading PALO in the mixed product order 299 is established by the material handling system 190 such that each pallet load PALO is a "storage friendly pallet" or a "storage friendly pallet load" . Here, "store friendly" means that the pallet load PALO is configured to be easily and efficiently unloaded and distributed to store shelves. For descriptive purposes only, "store friendly" means the store affinity of a pallet load or the pallet load store affinity such that the pallet load configuration (i.e., the pallet load establishment) includes predetermined characteristics (or factors) of the store affinity , this characteristic biases or affects the solution of each pallet load PALO such that each resulting pallet load PALO conforms to and provides retail store characteristics based on or compatible with the predetermined characteristics of the retail store, as will be described herein. For example, when the pallet load PALO (see Figure 2-4) of the completed mixed product order 299 arrives at the ordering store 200, the pallet load PALO (e.g., pallet load PALOC in Figure 2, PALOA in Figure 3, PALOA' and PALOC, PALOC' in Figure 4) are quickly unloaded (e.g., following inventory practices such as "just in time") and their goods are distributed (e.g., replenished/restocked) onto store shelves 233, while store operations minimal interference. In order to facilitate the rapid unloading and distribution of goods onto store shelves 233, the material handling system 190 is configured to establish a pallet load PALO such that the structure CU (also referred to herein as packages, products, cases, etc.) of goods loaded on the pallet PALO Units, mixed cases, cases, shipping cases, and case units) are grouped in a manner similar to how goods CU are assigned to store shelves 233 .

Each warehouse customer of warehouse 199 (eg, ordering store 200) may have its own preferences regarding handling pallet loads within ordering store 200. Aspects of the present disclosure provide for the creation of store-friendly pallets that correspond to the different ways warehouse customers handle pallet loads and product distribution.

Referring to Figure 2, an exemplary method of handling pallet load PALO may be referred to as a "clustered aisle pallet load package distribution method" and includes de-stacking/downstacking in the ordering store's loading dock area 222 (or other suitable area) The pallets load PALOC and place goods CU belonging to different parts of the ordering store 200 onto two or more separate secondary pallets PAL21-PAL23 (the three secondary pallets shown in Figure 2 are for example only. Purpose). These secondary pallets PAL21-PAL23 contain goods CU assigned to the predetermined shopping aisle and are moved to the corresponding predetermined shopping aisle for unloading (see Figure 2). With the secondary pallets PAL21-PAL23 in the corresponding shopping aisle, the goods CU from the secondary pallets PAL21-PAL23 are assigned to the designated shelves 233.

Referring to Figure 3, another example of handling a pallet load PALO may be referred to as the "adjacent aisle pallet load parcel distribution method" and includes the entire pallet load PALOA, PALOA' (e.g., stacked down without pallets ) moves into the shopping aisle. For the pallet loads PALOA, PALOA' in the shopping aisle, the goods CU are basically distributed directly from the pallet loads PALOA, PALOA' to the designated shelves 233 (see Figure 3). Here, goods are arranged on pallet loads PALOA, PALOA' in order to minimize the distance traveled within the store by each pallet load PALOA, PALOA' and essentially avoid pallets PALOA, PALOA' returning to the corresponding pallet A previously visited aisle (eg, the pallet has only crossed the aisle once along the predetermined path 301, 302). The goods CU can be arranged on the pallet loads PALOA, PALOA' according to the travel paths 300, 302 of the corresponding pallet loads PALOA, PALOA' through the shopping aisle.

Referring to Figure 4, yet another example of a handling pallet PALO may be referred to as a "Hybrid Mode Cluster and Adjacent Aisle Pallet Load Parcel Distribution Method" and includes a combination of the above processing methods. Referring to Figure 4, pallet loads PALOC, PALOC' arrive from the warehouse/distribution center 199 by truck (or other suitable transportation vehicle) to the ordering store 200. The pallet loads PALOC, PALOC’ are moved (without stacking the pallets downwards) to the shopping area near the shelf, and the goods CU on the pallet load PALOC, PALOC’ are assigned to the shelf. Since the pallet loads PALOC, PALOC’ are usually located near the designated shelves, the pallet loads PALOC, PALOC’ are stacked down to the corresponding secondary pallets PALO21, PALO22, PALO23, PALO21’, PALO22’ assigned to the corresponding shopping aisle. Here, the pallet loads PALOC, PALOC' are established such that each pallet load PALOC, PALOC' includes goods belonging/assigned to store aisles that are close to each other (e.g., pallet loads PALOC include items located in aisle 1, aisle 2 (with aisle 1 adjacent) and cargo in aisle 4 (just one aisle away from aisle 2; similarly, pallet load PALOC' includes cargo belonging/assigned to adjacent aisles 12 and 13). The goods CU may also be arranged in respective pallet loads PALOC, PALOC' such that the pallet structure corresponds to the way in which the goods are stacked down onto the respective secondary pallets (e.g. sequential stacking down, where e.g. assigned to the secondary The goods of pallet PALO21 are on the top of the pallet structure of pallet load PALOC, the goods allocated to secondary pallet PALO22 are in the middle of the pallet structure of pallet load PALOC, and the goods allocated to secondary pallet PALO23 are located on the pallet. The bottom of the pallet structure of the plate load PALOC). In this aspect, the aisles to which the cargo CU is allocated may not be arranged along respective specific paths (see, for example, paths 301, 302 in Figure 3) to unload the cargo CU of the corresponding pallet loads PALO, PALO' to On store shelves.

The above-described examples of processing/stack-down methods in the ordering store 200 are illustrative only. Again, note that the pallet loads PALOC, PALOC’, PALOA, PALOA’ for each pallet handling/stacking-down method are generally referred to herein as pallet loads PALO. It should also be noted that the pallet load PALO may be established by the material handling system 190 in any suitable manner such that shipments on the pallet load PALO are based on the ordering store affinity characteristics 166, 166' used for the pallet load package allocation method described herein. Arrange at least one order pallet of any suitable order. It should be noted that store-friendly pallet loading solutions (as described herein) are independent of storage array 130 placement of cases CU to stackers 162 and material handling system 190 throughput. Here, the output of totes CU from the storage array 130 is selected by the material handling system 190 to conform to or otherwise depend on (based on) the store affinity pallet load solution. In one or more aspects, the throughput of CU cases output by the material handling system 190 may be in a manner similar to U.S. Patent Application No. 17 entitled "Pallet Building System with Flexible Sequencing" filed on November 6, 2020 /091,265, the full disclosure of which is incorporated herein by reference. In accordance with aspects of this disclosure, the tote CU configuration within the storage array 130 can be freely optimized for optimal throughput, separate from the solution and establishment of store-friendly pallet load PALOs. An example of throughput optimization can be found in U.S. Patent No. 9,733,638 titled "Automated Storage and Retrieval System and Control System Therefor" issued on August 15, 2017, the disclosure of which is incorporated herein by reference in its entirety.

Referring to Figure 1, a material handling system 190 may be provided in a retail distribution center or warehouse 199, for example, to fulfill orders received from a retail store (e.g., ordering store 200 - see Figures 2-4) for shipping cases, Orders for restocked items shipped by parcel and/or postal parcel. The terms box, package and parcel are used interchangeably herein and, as previously stated, can be any container that can be used for shipping and that can be filled by a manufacturer with one or more product units. As used herein, a box or boxes refers to a box, parcel or mailing unit that is not stored on a pallet, tote, etc. (eg not contained). It is noted that the container unit CU may include a container of items/units (eg soup cans, cereal boxes, etc.) or individual items/units suitable for removal or placement on a pallet. In accordance with the present disclosure, current closure, container units (e.g., cartons, barrels, boxes, crates, jugs, shrink wrap pallets or groups, or any other device suitable for holding cargo) may be of various sizes and may be used in Cargo is stored in transit and can be configured to be stacked for transport. A case unit CU may also include one or more totes, boxes and/or containers of individual items, unpacked/retired from their original packaging (commonly referred to as unpacked items) and stored at the order filling station with one or more Other mixed or common types of individual items are placed together in totes, boxes and/or containers (collectively, totes). Note that, for example, incoming bales or pallet loads PALN (e.g., from a manufacturer or supplier of case units) arrive at the material handling system 190 to replenish merchandise stored within the storage array 130 within the material handling system 190 , the contents of each pallet load PALN can be uniform (for example, each pallet can hold a predetermined number of the same items - one pallet holds soup, another pallet holds cereal). It is understood that such pallet loads PALN loads may be of substantially similar condition, or in other words, homogeneous condition (e.g. similar dimensions), and may have the same SKU (otherwise, as mentioned earlier, the pallet may be of a "rainbow" of layers formed by homogeneous shells pallet).

As the pallet load leaves the material handling system 190 to fill store replenishment orders with totes or totes, the pallet load PALO may contain any suitable number and combination of different tote units (e.g., each pallet may hold different types of Cargo unit - a pallet holds a combination of canned soups, cereals, beverage packages, cosmetics and household cleaners). Cases combined onto a single pallet may be of different sizes and/or different SKUs.

Material handling system 190 generally includes a storage array 130 and an automated package transport system 195 . Storage array 130 includes storage spaces 130S for accommodating container units CU therein. Automated transportation system 195 is communicatively connected to storage array 130 for storing case units CU within storage space 130S of storage array 130 and for retrieving case units CU from storage space 130S of storage array 130 .

The automatic stacker 162, 162' includes an automatic package picking device 162D (e.g., a robotic arm, a gantry picker, etc.) capable of moving case units CU from a package storage section (such as an outbound transfer station 160) to a pallet (herein). (also called a pallet base) to form a pallet load PALO from a container unit CU, wherein the pallet load PALO includes a plurality of container units CU of composite layers L1-Ln. As described herein, a plurality of composite layers L1 - Ln of case units CU is composed of case units CU arranged in a pallet load PALO, which embodies a predetermined method of parcel distribution for the pallet load at the ordering store 200 At least one pallet has an ordering store affinity feature 166, 166' (see Figure 2-4). The automated stackers 162, 162' are communicatively connected to the automated package transport system 195. The automated package transport system 195 provides individual cases CU from the storage array 130 to the automated stacker 162 for forming a pallet load PALO, wherein the pallet load PALO includes a plurality of case units CU of composite layers L1-Ln. A single case unit CU from the storage array 130 is created from the pallet load PALO having a case size (eg, any one or more of case length, case width, and case height), where the case size has substantially Gaussian distribution or essentially random probability, represented by the normal probability curve shown in Figure 17. 17 is a chart illustrating variations in container dimensions (eg, length, height, and width) in a representative container population CU, such as may be found in a material handling system 190 and used in response to customer replenishment orders (as described herein). (described above) produces a mixed container pallet load PALO. As can be appreciated, an order may result in a mixed case pallet load PALO, including many cases with sizes from different parts of the size spectrum shown in Figure 17.

Controllers 164, 164' are operably connected to the automatic stacker 162. The controller 164, 164' is programmed with non-transient computer code defining the pallet load generator 165, 165' to have a predetermined method for pallet load PALO case unit CU distribution at the ordering store 200, at least one The pallet has ordering store affinity features 166, 166' (as will be described herein). As described herein, the pallet load generators 165, 165' are configured such that the case units CU of the pallet load PALO formed by the automatic stacker 162 are arranged in the pallet load PALO, reflecting the affinity of at least one pallet to the ordering store. characteristic.

Now in greater detail, and still referring to FIG. 1 , the material handling system 190 may be configured to be installed in an existing warehouse structure or adapted to a new warehouse structure, for example. As previously mentioned, the material handling system 190 shown in FIG. 1 is representative and may include, for example, in-feed and out-feed conveyors (e.g., from and to respective depalletizers 162' and stackers 162 transfer tote unit), which terminate in respective infeed and outfeed transfer stations 170, 160, lift modules 150A, 150B, storage array 130 (e.g., including suitable structures such as racks, vehicle running surfaces, storage racks, etc. ), and a number of autonomous transportation vehicles 110 (also referred to herein as "robots").

It should be noted that the material handling system 190 is formed by at least the storage array 130 and the robot 110 . In some aspects, the lifting modules 150A and 150B also form part of the material handling system 190; however, in other aspects, the lifting modules 150A and 150B can also form a vertical sorter in addition to the material handling system, such as 2020 This is described in U.S. Patent Application No. 17/091,265 titled "Pallet Building System with Flexible Sorting" filed on November 6, 2018, the disclosure of which is incorporated herein by reference in its entirety. In the alternative, material handling system 190 may also include a robot or robotic transfer station 140 that may provide an interface between robot 110 and lift modules 150A, 150B.

The storage array 130 includes forming a plurality of (stacked) storage layers 130L1-130Ln (see FIG. 1, often referred to as a number of storage levels 130L or storage layers 130L, and where n is an integer representing the storage layers present in the material handling system 190 any suitable structure of storage rack modules, wherein each level 130L includes a respective picking aisle 130A, storage space 130S and transport deck 130B for any storage space 130S and lift module 150A in the storage structure 130 , transfer container units between 150B racks. The storage spaces 130S are arranged along (or side by side) on one or more sides of each picking aisle 130A, so that the robot 110 traveling along the picking aisle 130A can access the storage spaces 130S on both sides of the picking aisle 130A.

In one aspect, the picking aisle 130A is configured to provide guided travel of the robot 110 (eg, along a vehicle travel surface VRSR that includes robot guidance features (eg, rails)), while in other aspects, the picking aisle is configured to provide unrestricted travel of the robot 110 Itinerary (e.g., along a vehicle travel surface VRSU with respect to the openness and uncertainty of robot 110 guidance/travel). The transport deck 130B has an open and nondeterministic robot support travel surface VRS along which the robot 110 travels under the guidance and control provided by the robot's steering (e.g., such steering is guided by one or more differential drive wheels, Steering wheels, etc.). In one or more aspects, the transport deck 130B has multiple aisles between which the robot 110 is freely transported to access the picking aisle 130A and/or the lift modules 150A, 150B. Pick aisle 130A and transport deck 130B also allow robot 110 to place case units CU into picking inventory and retrieve ordered case units CU. In the alternative, each storage level 130L may also include a corresponding robotic transfer station 140 that provides a container unit transfer interface between the robot 110 and the lift modules 150A, 150B.

The robot 110 may be configured to place case units CU of retail merchandise, such as those described above, into picking inventory in one or more levels 130L of the storage array 130 and then selectively retrieve the ordered case units CU to place the order. The case unit CU is shipped to, for example, the ordering store 200 (see, for example, Figures 2-4) or other suitable location.

Infeed transfer station 170 and outfeed transfer station 160 may operate with their respective lift modules 150A, 150B for bi-directional transfer of container units CU to and from one or more levels 130L of storage structure 130 . or multiple layers of 130L transshipment. It should be noted that although the lifting modules 150A, 150B can be described as dedicated inbound lifting modules 150A and outbound lifting modules 150B, in alternative aspects, each lifting module 150A, 150B can be used to lift materials from Transfer system 190 transfer container unit in and out. Similarly, while stackers 162, 162' may be described as dedicated (inbound) destackers 162' and (outbound) stackers 162, in the alternative, each stacker 162, 162' Can be used to transfer container units to and from the material handling system 190.

As can be appreciated, the material handling system 190 may include a plurality of infeed and outfeed lift modules 150A, 150B that may be accessed by, for example, a robot 110 of the material handling system 190 such that one or more tote units do not contain (for example, the container unit is not stored in the pallet) or already contained (in the pallet or tote) can be transferred from the lifting module 150A, 150B to each storage space 130S on the corresponding level 130L, and can From each storage space 130S to any one of the lifting modules 150A, 150B on the corresponding layer 130L. Robot 110 may be configured to transfer case units between storage space 130S (eg, located in pick aisle 130A or other suitable storage space/case unit buffer located along transport deck 130B) and lift modules 150A, 150B. Typically, the lift modules 150A, 150B include at least one movable payload rack that can move a cargo container unit CU between the infeed and outfeed transfer stations 160, 170 and the corresponding level 130L of the storage space 130S, where the cargo container Units CU are stored and retrieved. The lift module may have any suitable configuration, such as a reciprocating lift, or any other suitable configuration. Lift modules 150A, 150B include any suitable controller (such as controller 120 or other suitable controller coupled to controller 120, warehouse management system 2500, and/or stacker controller 164, 164') and may Forming a sorter or sorter in a manner similar to that described in U.S. Patent Application No. 16/444,592 entitled "Vertical Sorter for Product Order Fulfillment" filed on June 18, 2019 (the entire text of which is disclosed by reference incorporated herein).

The material handling system 190 may include a control system including, for example, one or more control servers 120 communicatively connected to the infeed and outfeed conveyors and transfer stations 170 via a suitable communications and control network 180 , 160, lifting modules 150A, 150B and robot 110. The communications and control network 180 may have any suitable architecture, which may include, for example, various programmable logic controllers (PLCs), such as for commanding the operation of infeed and outfeed conveyors and transfer stations 170, 160, lifting molds, etc. Group 150A, 150B and other suitable system automation. Control server 120 may include high-level programming that affects the materials management system (CMS) that manages the flow of containers through material handling system 190 .

Network 180 may also include suitable communications for enabling a two-way interface with robot 110 . For example, robot 110 may include an onboard processor/controller 1220. Network 180 may include suitable two-way communications suite to enable robot controller 1220 to request or receive commands from control server 120 to effectuate required transmissions of container unit CU (e.g., placing into or retrieving from storage location) and Information and data of the robot 110 required to be sent to the control server 120, including the robot 110 ephemeris, status and other required data.

As shown in Figure 1, the control server 120 may further be connected to the warehouse management system 2500 for providing, for example, inventory management and customer order fulfillment information to the CMS 120 level program. U.S. Patent No. 9,096,375, issued on August 4, 2015, the disclosure of which is incorporated herein by reference in its entirety, describes a suitable example of a material handling system arranged for housing and storing tote units.

Establishing a PALO pallet load based on at least one pallet pair ordering store affinity will be described in greater detail in this aspect of the present disclosure with reference to Figures 1-5. As discussed above, at least one pallet-to-order store affinity characteristic 166, 166' is at least one (eg, predetermined customer affinity) for a clustered aisle pallet load package allocation method (see, eg, Figure 2), adjacent aisle pallet Methods for plate load parcel distribution (see, for example, Figure 3), and methods for mixed-mode cluster and adjacent aisle pallet load parcels (see, for example, Figure 4). The at least one pallet-to-order store affinity characteristic 166, 166' may be stored in any suitable memory, such as the memory of the control server 120 and/or the stacker 162, 162', as described herein, and controlled by Servers 120 and/or stackers 162, 162' are utilized to generate the PALO pallet loads described herein. Unless otherwise stated, the term aisle as used below refers to the order store aisle to which the pallet load PALO is shipped.

Referring to Figures 1 and 5, an exemplary diagram of sample ordering for a pallet plan is shown (see Figure 5) and includes case units from one or more aisles of the ordering store 200 (Figures 2-4). In the exemplary sample ordering shown in Figure 5, the aisles are numbered 1-12. The total volume V1-V12 of the container units CU sorted for each corresponding aisle 1-12 is represented by the height of the corresponding bar in the figure (each bar corresponds to the corresponding aisle 1-12). The volumes V1-V12 are expressed as decimal units relative to the expected total volume Vp of the container unit CU at a full pallet load (e.g. a full pallet load has a maximum pallet load of length Lp, width Wp and height Hp size). The volume Vp is the maximum dimension Lp (length), Wp (width), Hp (height) (for example, the space allocated for the case unit CU on the pallet load) multiplied by the expected volumetric efficiency E of the packaged product on the pallet load The product of , where:

Generally, the dimensions (eg, length, width, height) of the cargo/carton unit CU are known, with the cargo/carton unit CU having a general rectangular parallelepiped shape. Here, the known dimensions of the container units provide a basis for determining the total volume Vp of the container units CU (eg, the combined volume of the container units CU assigned to any given pallet load). For example, according to the calculation method used to plan a single pallet load, the average total product volume on a pallet with dimensions Lp (length) x Wp (width) x Hp (height) is statistically approximately 0.8 for the pallet load The standard deviation of the volume of the outer boundaries is 0.03 (e.g., approximately 80% of the pallet volume is occupied by the goods, while the remainder is the empty space between the goods). The expected efficiency E depends on the computational methods of packing algorithms (such as those described in this paper), which for state-of-the-art packing algorithms (such as those described in this paper) and mixed products, containing boxes of various sizes, should generally exceed approximately value of 0.8.

Referring generally to Figure 5, it can be seen that some aisles 1-12 (see, eg, aisle 2) may have an expected (eg, maximum) total volume Vp that exceeds one pallet load PALO (eg, the volume V2 of aisle 2). The other aisles 1-12 may have corresponding volumes that are smaller or smaller (see volume V9 of aisle 9) compared to the expected total volume Vp. As described herein, in accordance with aspects of the present disclosure, the pallet load generator 165, 165' (eg, the control server 120 and/or the stacker 162, 162') is configured to order a store based on at least one pallet pair Affinity characteristics 166, 166' to resolve at least one pallet load PALO such that the pallet load PALO is one or more of the following:

With respect to maximizing at least one of the maximum pallet load volume Vp and the maximum pallet load weight Wmax,

Have the maximum number of packages in the minimum number of store aisles,

Produce a pallet load with a minimum quantity for each store order,

are generated such that, for each pallet load sent to the ordering store 200, the case units CU forming the pallet load represent the minimum number of ordering store aisles, and

is generated such that, for each pallet load sent to the ordering store 200, the resolved pallet load represents the minimum number of ordering store aisles.

With reference to Figures 1, 2, 5, 6, 7, 8, and 12, the pallet-to-order store affinity features 166, 166' for the clustered aisle pallet load package distribution method will be described in greater detail. The clustered aisle pallet load parcel distribution method minimizes (1) the number of pallets built from a given product set and (2) the average per-aisle pallet ratio RPA. The per-aisle pallet ratio RPA is determined by dividing the total number of product instances per aisle per pallet by the total number of aisles. The pallet ratio RPA of each aisle can be understood as the number of times the pallet load PALO will appear in any aisle, or the number of aisles where the pallet load PALO exists to be unloaded. This quantity is sought to be minimized (e.g., close to 1).

The pallet ratio RPA of each aisle can be represented by the pallet-aisle binary matrix PA, as shown in Figure 6. Here, the number of columns of the pallet-aisle binary matrix PA is equal to the number of aisles (for example, eight aisles are shown) and the number of columns is equal to the number of pallets planned for a given order (for example, eight is shown). (out of four pallets). If there is a product from aisle (i) in pallet (j), the elements of the pallet-aisle binary matrix PA[i,j] at column (i) and row (j) are equal to 1, otherwise column (i ) and the elements of the pallet walkway binary matrix PA[i, j] at row (j) are equal to 0. The pallet ratio RPA for each aisle is determined by the sum of all elements of the pallet-aisle binary matrix PA divided by the number of aisles in which the product exists in the order. It should be noted that if each aisle exists in only one pallet, the per-aisle pallet ratio RPA is equal to 1. The per-aisle pallet ratio RPA is higher when more products from certain aisles are spread across more pallets. If the products in each aisle are present in each pallet, then the per-aisle pallet ratio RPA is equal to the number of pallets. In the example shown in Figure 6, each aisle pallet ratio RPA is equal to 11/8 or 1.375. Here, each aisle pallet ratio RPA is greater than 1 because the product from aisle 1 is present in pallets 1 and 3, the product from aisle 6 is present in pallets 2 and 4, and the product from aisle 8 is in pallets 1 and 4.

In the clustered aisle pallet load package distribution method, all single aisle pallets are planned for aisles where the container unit CU volume exceeds the expected pallet volume Vp or the maximum pallet weight Wmax, as will be described in more detail in this article. The remaining pallets used to fill store orders are planned from the aisle combinations, where such planning is determined using a repeated double loop, as shown in Figure 12A, where for each aisle combination iteration IAi (e.g., nested within the broader Within the pallet building iteration Pj), the pallets are planned such that the volume Vc(IAi) is maximized relative to the expected pallet volume Vp (e.g., to minimize the number of pallets in the order) and the pallet ratio RPA of each aisle is minimized (e.g. to get close to 1). Here, the double-loop determination is repeated to traverse the aisle combination until the pallet to be scheduled is successfully scheduled (described in more detail below), and the pallets are traversed until the entire store order is consumed (e.g., the order is filled) and there are no more pallets in the store order. Then there are the unplanned (that is, not allocated to the pallet load) container units CU. Here, order store affinity features 166, 166' are informed by repeated dual loop determinations, where at least one loop associates order store aisles with each other. At least one other loop of the dual loop determination is repeated to determine the available combinations of ordering store aisles to resolve the arrangement of case units or package CUs in a given pallet load PALO. For example, Figures 7 and 12B illustrate the determination of a repeating double loop, the at least one pallet established based on the ordering store affinity characteristics, for a clustered aisle pallet load package distribution method described below.

Warehouse management server 2500 or control system 120 (or any other suitable controller of warehouse 199) receives the store order (Figure 12B, block 1200). The warehouse management server 2500 receives store orders, and the store orders are transmitted to the control server 120 through the network 180 or in any other suitable manner. The control server 120 instructs the automated package shipping system 195 to retrieve the ordered items from the storage array 130 for transportation to the stacker 162 . For example, the robot 110 is commanded by the control server 120 on one or more predetermined storage levels 130L1 - 130Ln to retrieve the ordered container unit CU from the corresponding storage level 130L1 - 130Ln of the predetermined storage space 130S. The robot transports the retrieved container units CU from the storage space 130S to the elevator 150B, so that the retrieved container units CU are output to the stacker through the outfeed transfer station 160 in a predetermined order. Here, the predetermined sequence of case unit CU outputs is determined at least in part by the ordering store affinity properties 166, 166'.

One or more control servers 120 and palletizers 162 are configured to determine the ordering store affinity characteristics 166, 166' For example, the stacker controller 164 of one or more control servers 120 and the stacker 162 are configured with pallet load generators 165, 165'. For example, in one aspect, each respective ordering store 200 may notify the pallet load generators 165, 165' of the corresponding pallet-to-ordering store affinity characteristics 166, 166' prior to placing the order (such as when the ordering store is opened with the warehouse 199 When the account number, or at any other suitable time, and the pallet is communicated or entered into the warehouse management system) for the ordering store affinity feature 166, 166'). Here, the pallet load generator 165, 165' may include any suitable table that associates each ordering store 200 with a corresponding pallet for the ordering store affinity properties 166, 166'. In other aspects, the pallet-to-ordering store affinity 166, 166' may be communicated to the pallet load generator 165, 165' at the same time the order is placed (such as an item in the order submission, where the pallet load generator The pallet-to-ordering store affinity properties 166, 166' are determined directly regardless of the identity of the ordering store 200). As mentioned above, in this example, the pallet-to-order store affinity properties 166, 166' are used for the clustered aisle pallet load package distribution method.

The pallet load generator 165, 165' determines any aisle (FIG. 7 block 700A) that has a total volume of tote units Vcomb greater than the expected volume Vp of the pallet load PALO (in the example shown in FIG. 5, aisle 2's The volume V2 is greater than the expected volume Vp). Optionally, the pallet load generator 165, 165' identifies any aisle where the total weight of the container units Wcomb is greater than the expected weight Wmax (eg, maximum weight) of the pallet load PALO. Based on the presence of any aisle with a total volume of container units Vcomb greater than the expected volume Vp or with a total weight Wcomb of container units greater than the expected weight Wmax (collectively referred to herein as "excess aisles"), pallet load generators 165, 165' The planned pallet load PALO is formed entirely from the tote units ordered and belonging to the excess aisle (block 710 in Figure 7). In some aspects, there will be some container units CU in the excess aisle (block 720 in Figure 7), with the remaining container units included in the subsequent pallet load. For example, the pallet load generators 165, 165' form a pallet load 1 (see Figure 8) having a portion V2A from the container unit volume V2 of Figure 5 and the remaining portion from the container unit volume V2 of Figure 5 V2B is included in Pallet Load 5 as described below.

Subsequent pallet loads (or pallet loads without excess aisles) are planned from one store aisle or a combination of store aisles. As described herein, the aisle combinations are calculated by the pallet load generators 165, 165' to minimize the pallet ratio of each aisle and maximize the container unit volume of each pallet load PALO. Here, each available aisle combination of ordering store aisles is determined based on maximization of pallet load, or other aspects described herein, based on maximization of pallet load and continuity or contiguity of aisles in the available combinations. Determine the combination in which pallet loads are maximized with a higher weight than walkway continuity or adjacency.

The total volume Vcomb of the container units for each subsequent pallet load is less than the expected product volume Vp of the pallet load PALO, and the total weight Wcomb of the container units is less than the expected weight Wmax of the pallet load PALO. Each aisle combination can have a different number of aisles, ranging from one aisle to the total number of aisles remaining in the order. The list of allowed aisle combinations ALC (see Figure 1) can be determined by employing the binary representation of an integer iterator (block 730 of Figure 7), where the value k of the integer iterator ranges from 1 to 2 ^Na -1, where Na is the number of aisles remaining in the order. Each increment of this integer iterator corresponds to a potential combination of aisles, as follows: If the m-th bit of the least significant bit of the binary representation of the integer iterator is 1, then there is an aisle in the list of remaining aisles in the combination m, if the least significant bit is 0, then aisle m does not exist in the combination.

As an example of using an integer iterator, assume a store order has 5 aisles (there may be more or less than 5 aisles), and the integer iterator equals 12, which is the 12th iteration (note that in 31 iterations Iteration 11 may occur before iteration 12 (where in this case the integer iterator ranges from 1 to 31, determined by k=2 ^Na -1=2 ⁵ -1=31 iterators/iterations), and There may be subsequent iterations after iteration 12, such as where the aisle remains in the sequence). The binary representation of the number 12 (that is, an integer iterator) is 01100. The number of lanes is in order from high to low, and can be arranged in a grid relative to the binary representation of the integer iterator (so that the number of the lanes aligns with the corresponding number in the binary representation of the integer iterator), as shown below : Aisle number 5 4 3 2 1 bit value of integer iterator 0 1 1 0 0

As mentioned above, if the bit of the integer iterator corresponding to an aisle is 1, then the case unit CU from that aisle is present in the aisle combination. In the example provided above, the bits of the integer iterators corresponding to aisles 4 and 3 are 1, which means that the case units CU in aisles 4 and 3 are included in the 12th iteration combination of aisles, while aisle 5 , 2 and 1 are excluded from the 12th iteration combination of the aisle.

For each value k of the integer iterator, the total volume Vcomb and the weight Wcomb of the container unit CU in the corresponding aisle are determined and compared through the pallet load generator 165, 165' (for example, the corresponding value of the given value k of the integer iterator Aisle combination) with expected pallet volume Vp and maximum pallet weight Wmax. If any value of Vcomb and Wcomb exceeds the values of Vp and Wmax respectively, then the aisle combination in which at least one Vcomb and Wcomb value exceeds the Vp and Wmax values will be discarded. If the values of Vcomb and Wcomb are smaller than the values of Vp and Wmax respectively, the aisle combinations whose values of Vcomb and Wcomb are both smaller than Vp and Wmax are added to the allowed channel combination list ALC. Referring to the above example, the combined volumes V3 and V4 of aisles 3 and 4 must be less than or equal to the expected pallet volume Vp, respectively, and the total weights W3 and W4 of aisles 3 and 4 must be less than or equal to the maximum pallet weight Wmax, respectively, in order to be included in Allowed aisle combinations are on the ALC list.

The list of allowed aisle combinations ALC may be ordered in any suitable way, such as in descending order of the total (carton unit) volume Vcomb of each aisle combination. Sorting the list of allowed aisle combinations in descending order of total case volume Vcomb provides the minimum number of pallets for a given store order. Here, the allowed aisle combination list ALC is used as a candidate combination list for selecting products in the output pallet list for a given store order for planning the pallet load PALO.

Allowed Aisle Combinations A sample ordered list of the ten aisles of the ALC could look like this: Aisle combination 1 Aisles 2, 3, 8 Vcomb/Vp = .99 Aisle combination 2 Aisles 1, 4, 6, 9 Vcomb/Vp = .98 Aisle combination 3 Aisle 3, 7 Vcomb/Vp = .98 Aisle combination 4 Aisles 4, 5, 10 Vcomb/Vp = .96 The rightmost column represents the total volume ratio of the container units of each aisle in the aisle combination relative to the expected pallet volume Vp (for example, the combined volume Vcomb).

It is noted that in the event that the number of aisles included in the store order is large, each aisle may be subdivided into any suitable number of aisle subdivisions, where the size of the aisle subdivisions may depend on the pallet load generator 165, 165' computing resources. The size of the aisle subdivisions may also affect the minimum number of pallets produced/outputted by the warehouse 199 for a given store order. Aisle subdivisions can be grouped with other aisle subdivisions to form store partitions, where each aisle subdivision is considered an aisle, and the aisle combination list ALC determines each store partition in the manner described above.

As mentioned above, notification of the pallet-to-ordering store affinity feature for the clustered aisle pallet load package allocation method is determined by repeating the dual-loop DRL, where at least one loop determines the available combinations of ordering store aisles, parsing the packages in the pallet load. arrangement, and at least one other loop will order the store aisles interconnected. In repeated double circuits, DRL pallet loads are planned using the aisle combination list ALC.

In one loop of the repeated dual loop DRL, the pallet load generators 165, 165' determine the available aisle combinations that resolve the package placement in the pallet load (Figure 12B block 1230). Select an item from the aisle combination list ALC with the highest Vcomb/Vp ratio (in the example above it is aisle combination 1) (Figure 7 block 735) and use the bin corresponding to the aisle in the selected aisle combination The unit CU plans the pallet load PALO (block 740 in Figure 7) to optimize the minimum number of pallets. If the pallet plan of the selected aisle combination does not fit all the case units in the aisles in the selected aisle combination in the pallet load PALO (this means that some case units of the corresponding aisle are still not packed for inclusion in other pallets, Confirm or verify the optimization of the pallet ratio RPA for each aisle - block 745 of Figure 7), then the pallet plan is discarded (block 750 of Figure 7). Select the next item from the ALC list of aisle combinations with the next highest Vcomb/Vp ratio (e.g., the next aisle combination, in the above example, aisle combination 2) (Figure 7 block 735), again minimizing the minimum threshold. Optimize the number of plates. The pallet load PALO is planned using the tote unit CU corresponding to the aisle in the next aisle combination (Fig. 7 block 740), where blocks 740, 745, 750, 735 are repeated (for subsequent aisle combinations, for example, aisle combination 2 , aisle combination 3, aisle combination 4, etc.) until the pallet planning list ALC of the item selected from the aisle combination list successfully packs all the case units of the corresponding aisle in the pallet load (for example, pallet load PALO), confirm again Or verify the optimization of pallet ratio RPA for each pallet aisle. Here, by repeating the dual-loop DRL determination, the aisle combinations are analyzed sequentially by the pallet load generators 165, 165' until a planned solution is found that will include all tote units ordered for the aisles in the aisle combination.

As an example of aisle combination sequence analysis, using aisle combinations 1-4 above, the pallet load generator 165, 165' first analyzes aisle combination 1 (aisles 2, 3, 8) to determine all orders for aisles 2, 3, and 8 Whether the cargo container unit CU is suitable has a maximum volume Vp and a maximum weight Wmax. For example purposes, assume that not all ordered tote units for aisles 2, 3, and 8 will fit one pallet load, so analyze the next aisle combination in the sequence of aisle combinations (e.g., aisle combination 2). Here, the pallet load generator 165, 165' analyzes aisle combination 2 (aisles 1, 4, 6, and 9) to determine whether all ordered case units CU of aisles 1, 4, 6, and 9 fit into one with the maximum volume Vp And the pallet load of the maximum weight Wmax. For illustrative purposes, it is assumed that all ordered tote units for aisles 1, 4, 6, and 9 fit one pallet load, therefore, subsequent determination loops analyzing aisle combinations will stop and the remaining aisle combinations (e.g., aisle combination 3 and 4). As described below, any subsequent pallet loads will be generated using an updated set of aisle combinations (separate and distinct from the previous aisle combination and excluding aisles to which all ordered tote units have been assigned to the pallet load).

The successful pallet plan (aisle combination 2 in the example above) forms the planned pallet load PALO and is added to the output list (block 755 of Figure 7) executed by the automated parcel shipping system 195 such that the automated parcel shipping system 195 Pick and sort case units CU in the planned pallet load PALO (Figure 12B block 1220) for establishing the planned pallet load at the stacker 162 (Figure 12B block 1250). In some aspects, case unit picking and pallet building for a given store order may occur substantially concurrently with the planning of subsequent pallet loads in that store order, while in other aspects, case unit picking and pallet building may Occurs after all pallets have been planned for the store order.

In another loop repeating the dual loop DRL, where the planned pallet load PALO is successfully planned, the pallet load generator 165, 165' determines if there are any case units CU from any aisle in the store order that are not included (successfully ) in the planned pallet load PALO (block 760 in Figure 7). In the absence of more case units CU, pallet planning is stopped (Fig. 7 block 765) and the case units CU for the planned pallet load PALO are retrieved from storage and sorted by the automated parcel shipping system 195 (Fig. 12B Block 1220), and the pallet load PALO is established by the stacker 162 (Block 1250 of Figure 12B). If the case unit CU still exists, another (eg, subsequent) pallet is scheduled to be included in the store order (Figure 7 block 770). Here, the pallet load generator 165, 165' updates the relationship between store aisles (Figure 12B block 1240; Figure 7 block 730) such that all aisle combinations containing any aisles where the previous pallet was fully consumed (e.g., All ordered tote units whose aisles have been assigned to pallet loads are removed and an updated aisle combination list ALC is generated (block 730 of Figure 7). Repeating the dual-loop DRL will continue until there are no unscheduled case units CU in any aisle of the store order (i.e., all ordered case units are assigned to the pallet load). The pallet load generators 165, 165' are configured to associate each store aisle with one another (Fig. 12B block 1240, see also Fig. 7 block 730 described herein) to minimize the total number of pallet loads in an order and/or Minimize the pallet ratio RPA of each aisle. It is important to note that, as described in this article, the term "aisle" as used in this article generally refers to ordering store aisles and product groups assigned integer values. Thus, order store aisles (eg, physical locations in the order store) are related to each other through at least one of an aisle-to-aisle affinity property and a product group type to product group type affinity property.

Figure 8 is an exemplary store order 800 plan with pallet load generators 165, 165' employing the clustered pallet load package aisle allocation method described above. In this example order 800, the volume of tote units in each aisle shown in Figure 5 is shown included in the corresponding pallet load (eg, Pallet 1 - Pallet 6), where each pallet The plate loading is planned sequentially (as described above) so as to have a volume Vcomb that is less than the maximum pallet volume Vp. As can be seen from Figure 8, the volume V2 corresponding to the case unit CU ordered for aisle 2 is divided between pallet loads 1 and 5 (as described above), so that pallet load 1 is occupied by the cases ordered for aisle 2 The unit is completely consumed. Note that the last planned pallet load (e.g., pallet load 6) may have a smaller combined volume Vcomb than the previously planned pallet load (e.g., pallet loads 1-5) because the final pallet load includes the previously planned pallet load Carton units for aisles not included in previous aisle combinations of planned pallet loads 1-5, previously planned pallet loads optimized for volume or weight, optimized for minimum pallet count and/or The pallet ratio RPA of each aisle is optimized.

Following the clustered aisle pallet load package distribution method, the resulting pallet load PALO is created by the stacker 162 and transported (block 1260 in Figure 12B) to the ordering store 200. The pallet load PALO arrives from the warehouse 199 at the ordering store 200. Referring to Figure 2, pallet loads PALO are typically received at the ordering store 200 in the loading dock area 222. Each pallet load PALO includes products from several physical locations of the ordering store 200 (eg, aisles, departments, sections, etc.). For illustrative purposes, these physical locations are referred to herein as walkways. It is noted that although aisles 1-4 and aisles 11-14 are shown in Figure 2, the ordering store may have any suitable number of aisles. In a clustered aisle pallet load package distribution method, the case units CU stored on the pallet load PALO (e.g., manually or with automated unloading, such as those similar to those described herein with respect to the stackers 162, 162' Palletizer) unloads pallet loads PALO from pallet loads PALO to separate and distinct secondary pallet loads PALO21, PALO22, PALO23 (three are shown for example purposes, it will be understood that there may be more or less than three secondary pallet load). Here, each secondary pallet load PALO21, PALO22, PALO23 includes a container unit CU from a separate single aisle. For example, pallet load PALO21 only includes container units CU assigned to aisle 1, pallet load PALO22 only includes container units CU assigned to aisle 3, and pallet load PALO23 only includes container units CU assigned to aisle 12. Secondary pallets PALO21, PALO22, PALO23 (e.g., manually and/or with automatic conveying) are moved from the loading dock area 222 to corresponding designated aisles in the shopping area 224 of the ordering store 200, with each secondary pallet loading PALO21, The container units CU of PALO22, PALO23 are unloaded and placed on corresponding store shelves 233 in corresponding designated aisles.

In a clustered aisle pallet load package allocation method, the pallet load PALO may accommodate case units CU allocated to aisles that are remote (eg, far away) from each other in the ordering store 200 . As mentioned above, the cargo box units CU assigned to the corresponding aisles are unloaded onto the corresponding secondary pallet loads PALO21, PALO22, PALO23, so that the pallet loads PALO cargos assigned to the aisles are spatially distant from each other (for example, far away). Case units CU have essentially little impact on the replenishment/stocking of store shelves 233 . Here, in the clustered aisle pallet load parcel allocation method, container units CU from different aisles can be allocated to a common pallet load PALO (regardless of whether the aisles are close or not) to maximize the number of full-size pallet loads (e.g., with pallet load that maximizes the pallet load size and/or weight) and minimizes the number of pallet loads PALO on the transport vehicle that moves the pallet load PALO from the warehouse 199 to the ordering store 200 .

Referring now to Figures 1, 4, 5, 9, 12, and 13, the pallet-to-order store affinity characteristics of the mixed-mode cluster and adjacent aisle pallet load package distribution methods will be described in greater detail. The mixed-mode cluster and adjacent aisle pallet load parcel allocation method minimizes (1) the number of pallets established from a given set of products and (2) the average per-aisle pallet ratio RPA, while minimizing the allocation to The distance between the rack locations of the case units for each pallet. For purposes of description, aisle numbers that are numerically close to each other are also spatially close to each other (eg, aisles 10 and 11 are close to each other, while aisle 60 is further away from both aisles 10 and 11 ). The clustered aisle pallet load parcel allocation method described above is modified here to allow pallet loads to be planned (e.g., based on the continuity or adjacency of one ordering store aisle to another ordering store aisle), where in ordering store 200 , products on common pallets are unloaded into aisles that are continuous or adjacent to each other.

In hybrid mode, cluster and adjacent aisle pallet load package allocation methods are ordered by the ordering store 200 and at least one store ordering affinity characteristic is determined in the manner described above for blocks 1200 and 1210 of Figure 12B. Blocks 700A, 700B, 710, 720 of Figure 13 are the same as the similarly numbered blocks in Figure 7 . Therefore, the entire pallet is planned from the aisles where the container unit volume is greater than the pallet load volume Vp and/or the weight is greater than the maximum pallet load weight Wmax, where the remaining container units ordered for these aisles are included in the aisle combination analysis in the manner described above (Figure 13 blocks 700A, 700B, 710 and 720). Aisle combinations for the mixed-mode cluster and adjacent aisle pallet load package distribution methods are also determined in the manner described above for block 730 of Figure 7 (see also block 1220 of Figure 12B); however, the determined aisle combinations are ordered by score S, It takes into account the volume of the ordered case units for a given aisle, the weight of the ordered case units for a given aisle, and the tightness of the aisles contained in the plan pallet (Figure 13 block 1330). For example, the score S can be determined by the following formula:

where minAisle and maxAisle are the minimum and maximum aisle numbers contained in a given aisle combination, and d0 is greater than 0 and is a parameter reflecting the relative importance of aisle distribution/distance (e.g., store friendliness) versus case volume in the pallet load. As can be seen from Equation 2, for smaller values of d0, the aisle distribution/distance is more important than the volume of the bins in the pallet load, and for larger values of d0, the volume of the bin units, the volume of the bins in the pallet load Bin volume is more important than distribution/distance between aisles allocated to pallet loads. The determined aisle combinations (see block 730 of Figure 7) are weighted or scored by the score S and ranked according to the score S (see block 1330 of Figure 13). Repeat the dual loop DRL in the manner described above for blocks 735, 740, 745, 750, 755, 760, 765, 770 of Figure 7 (see also block 1230 of Figure 12B) for planning the pallet so that the minimum pallet The number of pallets is optimized and the optimization of the pallet ratio RPA for each aisle of the pallet is verified/confirmed; however, for each subsequent pallet, the updated aisle combination is again scored using the score S and sorted according to the score S. The ordered case units are picked, the planned pallet load PALO is established and shipped to the ordering store in the manner described above in blocks 1240, 1250 and 1260 of Figure 12B.

Figure 9 is an illustrative example of planned pallet loads (eg, Pallet 1 - Pallet 7) determined using a mixed-mode cluster and continuous aisle pallet load parcel allocation method. In this illustrative example, the planned pallet load is determined based on an order with the aisles and corresponding tote unit volumes shown in Figure 2. As shown in Figure 9, the first pallet load is planned separately from the bin unit volume V2A portion of aisle 2, while the volume Vcomb of all other planned pallet loads in the store order is less than the expected volume Vp of the pallet load (as above described). According to the pallet load parcel allocation method for mixed-mode clusters and adjacent aisles, the planned pallet load 1 only includes the volume of tote unit V1 allocated to aisle 1. Planned pallet load 2 includes the volumes allocated to tote units V2B and V3 in aisles 2 and 3. Planned pallet load 4 includes the volumes of tote units V4 and V7 allocated to aisles 4 and 7. Note that planned pallet load 4 creates an interruption in the series of aisles, but this interruption is not large because aisle 4 is only 10 meters away from aisle 7. 3 aisles, this meets the objectives of a mixed mode cluster and adjacent aisle pallet load parcel distribution approach. The planned pallet load 5 includes the volumes allocated to the tote units V5 and V6 of aisles 5 and 6 . The planned pallet load 6 includes the volume of the container units V8-V11 allocated to the aisles 8-11. The planned pallet load 7 includes the volume of the container unit V12 allocated to the aisle 12 .

Referring also to Figure 14, in some aspects of mixed-mode aggregation and adjacent aisle pallet load parcel distribution methods, it is common to express the difference between aisle numbers as the maximum (or average) distance MDmax between aisles, for any distribution to The order case unit CU for a given pallet may be specified by the ordering store 200 . This aspect of the pallet load parcel allocation method for mixed-mode clusters and adjacent aisles is the same as above; however, aisle combinations that include aisles with distances between aisles greater than the maximum distance MDmax are excluded before sorting the list of aisle combinations /discard (see block 1430 in Figure 14).

As described herein with respect to Figure 15, in other aspects of the mixed mode aggregation and adjacent aisle pallet load parcel distribution method, the pairwise relationship between aisles p and q may be specified by the ordering store 200. The relationship between aisles p and q can be expressed as an aisle affinity matrix A[p, q], where p and q belong to the set of all aisles that exist in order. The aisle affinity matrix A[p, q] is diagonally symmetric, so A[p, q] is equal to A[q, p]. For "store-friendly" aisles, the value of the aisle affinity matrix A[p, q] should be substantially equal to or close to 1, so that the case units CU of these aisles should be located on the same (e.g., single) pallet load. For "unfriendly" aisles, the value of the aisle affinity matrix A[p, q] should be basically equal to or close to 0, and the aisles should maintain separate container units CU under different pallet loads (as mentioned above, corrosive products ( For example, washing powder) and food products (for example, baby food). The diagonal elements of the walkway affinity matrix A[p, q] should be equal to 1, for example, for every p, A[p, p] = 1, which means that any walkway is friendly to itself.

Using a pairwise relationship between aisles, the mixed-mode cluster and adjacent aisle pallet load package allocation method is as described above; however, the fraction S is modified as follows:

for all {p, q} belonging to a given aisle combination. In Equation 3, the expression p is greater than or equal to 0 and is a multiplier showing the relative importance of pallet volume (e.g. minimization of the total number of pallets) and the friendliness between the aisles included in a given aisle combination. sex. For smaller p-values, aisle friendliness is less important than minimizing the total number of pallets, whereas for larger p-values, aisle friendliness is more important than minimizing the total number of pallets. In the manner described above (see Figure 13), the determined aisle combinations are scored and sorted in descending order according to the scores, starting with the first aisle combination in the aisle combination sorted list, and pallet loads are planned for each sequential aisle combination until the plan is successful pallet load, again optimize the minimum number of pallets and verify/confirm the optimization of the pallet ratio RPA for each aisle.

The pallet-to-ordering store affinity feature for the adjacent aisle pallet load package distribution method will be described in greater detail with reference to Figures 1, 3, 5, 10, 11, 12, and 15. The adjacent aisle pallet load package allocation method for pallet planning can be used by warehouse customers who transport ordered pallets to store aisles to unload case units from ordered pallets directly to store shelves. Here, as shown in Figure 3, each ordered pallet load PALOA, PALOA' is transported from one aisle to another along a respective transport path 300, 302 to unload the container units. The transport paths 300, 302 traverse the aisles in a continuous sequence of aisles (eg, pallet load PALOA traverses continuous aisles 1-3 and pallet load PALOA' traverses continuous aisles 11-13).

In the adjacent-aisle pallet load parcel allocation method, priority is given to selecting continuous or adjacent aisles when planning pallet loads while minimizing the total number of pallets planned for any given order and generally avoiding between pallets. The aisles are excessively split. If a walkway is split between two pallets, no more than one walkway will be split between the two pallets. Figure 10 shows an exemplary illustration of pallet loads planned using a "pure" adjacent aisle pallet load parcel distribution method. As with other pallet load parcel distribution methods, an aisle with a predetermined volume Vp greater than the pallet load (or a weight greater than the maximum weight Wmax of the pallet load) is selected and distributed to the entire pallet (see Figure 5, where aisle 2 The volume V2 is greater than the volume Vp (pallet load) until the remaining volume or weight in the corresponding aisle is less than the volume Vp or weight Wmax. As shown in Figure 10, the pallet load 1 is completely consumed by a portion V2A of the volume V2 of the aisle 2. As described in this article, in the case where full loads are planned to be loaded from excess aisles, all remaining volumes and weights of the aisles in the sequence (e.g., the volumes and weights of the boxes ordered for each corresponding aisle) are less than the volume of the pallet load Vp and Weight Wmax. Therefore, each aisle has a number of tote units that are expected to accommodate a single pallet load and, in many cases, are used in conjunction with other tote units from other aisles in a single pallet load, thus minimizing pallet load reduction. Number of boards and pallet ratio RPA for each aisle.

In the adjacent aisle pallet load package allocation method, the total number of pallet loads in the order and the per-aisle pallet ratio RPA are minimized, but compared to the allocation of case units CU to pallets in the continuous/adjacent aisle sequence. , to a lesser extent (e.g., each available combination of ordering store aisles is determined more based on continuity or contiguity of ordering store aisles in the available combinations and less based on pallet load maximization (volume or weight)). When pallet loads are planned based on the pallet load parcel distribution method for adjacent aisles, some aisles can be split between pallets, but only if splitting is avoided resulting in additional pallets, adding to any given The total number of pallets planned for the order.

If splitting aisles between pallet loads is not allowed, the total number of pallets may increase. For example, Figure 11 shows a store order using an adjacent aisle plan pallet load parcel distribution method (e.g., as shown in Figure 2) without separating case units from aisles between pallet loads (any excess aisles Except, for example, Aisle 2, where a portion of each aisle's tote units are consumed by the entire pallet load and the remainder of the tote units are distributed among the remaining pallet loads according to the adjacent aisle pallet load parcel distribution method). In Figure 11, the resulting order plan includes 7 pallet loads, which is the same number of pallet loads as the mixed-mode cluster and adjacent aisle pallet load parcel allocation methods, but more than the clustered aisle pallet load parcel allocation method One pallet load (note that the allocation method is based on the example of the unit sequence for the aisle shown in Figure 5). It should also be noted that, as shown in Figure 11, without splitting the aisles between pallet loads, the container unit volume of more pallets is lower than the maximum volume Vp of the corresponding pallet load, while in In the mixed mode, the container unit volume of the cluster and adjacent aisle pallet load parcel allocation method and the cluster aisle pallet load parcel allocation method (except for the last planned pallet load) is closer to the allowable volume Vp of the pallet load.

In order to increase the average pallet volume and reduce/minimize the number of planned pallets while prioritizing continuous/adjacent aisle planning (e.g. store friendliness), perform splitting of case units CU with certain aisles in pallet planning . Here, the adjacent aisle pallet load package distribution method can be "modified" to adopt the threshold values Vp0 and Vp1, where:

The values of Vp0 and Vp1 optimize the combination of pallet volume (and minimize the number of pallets) and the number of split aisles. The values of Vp0 and Vp1 should be reasonably close to Vp, for example:

and

The values of Vp0 and Vp1 generally remain constant (e.g. do not change during the pallet planning iteration loop described here), but can be adjusted for specific order profiles. For example, very large tote units may need to reduce Vp0 and Vp1 because some tote units are more likely to not fit a given pallet load, while small tote units may need to increase Vp0 and Vp1 because shipping tote units are more likely to be unsuitable for a given pallet load. May be suitable for given pallet load.

In the adjacent aisle pallet load wrapping method, an order is placed by the ordering store 200 and at least one store order affinity characteristic is determined in the manner described above for blocks 1200 and 1210 of Figure 12B. As mentioned above, a walkway with a predetermined volume Vp greater than the pallet load (or a weight greater than the maximum weight Wmax of the pallet load) is selected and assigned to all/entire pallets. The pallet quantity Np0 of the order is determined by the pallet load generator 165, 165' based on the remaining container unit volume Vrem and weight Wrem and the expected product volume Vp and maximum weight Wmax in one pallet load (block 1500 of Figure 15) , according to the following formula:

Pallet load generators 165, 165' relate aisles to each other (Figure 12B block 1220, in this example sequential aisle relationships) and determine aisle combinations, resolving tote unit placement in the pallet load (Figure 12B block 1230 ). For example, the pallet load generator 165, 165' determines the aisle combination for the "next" pallet load (block 1505 of Figure 15, where the "next" pallet load is the pallet load currently being planned). Here, the aisles are selected sequentially (e.g., i, i+1, i+2...), and for each added aisle (block 1510 in Figure 15), the cumulative container unit volume Vcomb and the cumulative Pallet weight Wcomb (block 1515 in Figure 15). The cumulative volume Vcomb is less than or equal to Vp0, the cumulative weight Wcomb is less than or equal to Wmax (block 1520 in Figure 15), and the next aisle in the aisle sequence is added to the aisle combination (block 1510 in Figure 15) to achieve verification/confirmation of each Aisle pallet ratio RPA optimization. Walkways are added to the walkway combination in sequence until one of the cumulative volumes Vcomb exceeds the value Vp0 and the cumulative weight Wcomb exceeds the maximum pallet load weight Wmax.

When one of the accumulated volumes Vcomb exceeds the value Vp0 and the accumulated weight Wcomb exceeds the maximum pallet load weight Wmax, the remaining product volume Vrem and the remaining product weight Wrem will be updated (block 1530 in Figure 15). The updated estimate of the pallet quantity Np1 of the order is determined by the pallet load generator 165, 165' in a manner similar to that described above, but using the updated values of Vrem and Wrem (i.e., in the area of Figure 15 of the first nested loop RL1 The remaining volume and weight after the last aisle selected in block 1510, including blocks 1510, 1515, 1520 in Figure 15, and nested within the overall/wider representation shown in blocks 1500-1580 and 1590 of Figure 15 in the loop), as shown below:

If the total number of pallets Np0 determined before selecting an aisle for the next pallet load is the same as the updated number of pallets Np1 (i.e., Np0 = Np1 + 1, where the number 1 represents the current pallet) (Figure 15 block 1536), Then stop selecting aisles for the next pallet load and load pallets from the aisle combination plan (Figure 15 block 1565), optimizing for the minimum number of pallets.

When the updated number of pallets Np1 increases (i.e., Np0 < Np1 + 1), other aisles in the aisle sequence are added to the aisle combination in the second nested loop RL2 (block 1540 in Figure 15). Nested loop RL2 includes blocks 1540, 1545, 1550, 1555, 1560 of Figure 15 and is nested within the overall/broader loop shown in blocks 1500-1580 and 1590 of Figure 15. As the next sequential aisle is added to the aisle combination (Figure 15 block 1540), the cumulative case unit volume Vcomb and the cumulative pallet weight Wcomb will be updated (Figure 15 block 1545). The remaining volume Vrem and remaining weight Wrem of the container unit in the order are also updated (block 1550 in Figure 15). The pallet load generator 165, 165' determines an updated estimate (block 1555 of Figure 15) of the order's pallet quantity Np1 (updated) in the manner described above (see Equation 8), but using the Updated values of Vrem and Wrem. Here, if any of the following conditions are not met (Equations 9-11), iterative loop RL2 is repeated, adding additional aisles to the aisle combination:

or

If any of the above conditions are met (Equations 9-11), then stop selecting aisles for the next pallet load and plan the pallet load from the aisle combination (Figure 15 block 1565), again optimizing for the minimum number of pallets. Better.

In the case of planned loading pallets (Figure 15 block 1565), unplanned products from the aisle combination (e.g., split aisles, e.g., aisle 6 divided into container unit volumes V6A, V6B and divided into container unit volumes Aisles 12) of V12A, V12B are added to the remaining products in the order (block 1570 of Figure 15). The pallet load generator 165, 165' adds the planned pallet load (from Figure 15 block 1565) to the output list of pallet loads (Figure 15 block 1575), affecting the creation of the pallet load in the output list. The pallet load generator 165, 165' determines whether there are any case units CU remaining in the order (block 1580 in Figure 15), again validating/confirming the optimization of the pallet ratio RPA for each aisle. In the absence of more tote units, stop the order's pallet load planning (Figure 15 block 1585) and establish the pallet loads PALOA, PALOA' and ship in the manner described above in Figure 12B blocks 1240, 1250 and 1260 Go to order store 200. If the container unit CU is retained in this order, its pallet count is updated (block 1590 in Figure 15) and another pallet is planned for the order in the manner described above, thereby minimizing the number of pallets.

In the adjacent aisle pallet load package allocation method described above, making the volume of the selected container unit higher than the first threshold volume Vp0 can increase the probability that at least one aisle is not fully packed into the pallet load currently being planned, Such that at least a portion of one aisle will overflow into the next planned subsequent pallet load. Tote unit spillage from one pallet load to the next subsequent pallet load will increase the value of each aisle pallet ratio RPA and may reduce aisle adjacency (e.g., overall store friendliness of ordering pallet loads). As mentioned above, the values of Vp0 and Vp1 can be adjusted to reflect the importance of minimizing the ratio RPA of total pallets to pallets per aisle. Higher values of Vp0 and Vp1 (e.g., closer to Vp) may reduce the expected number of pallets, while lower values of Vp0 and Vp1 may reduce the likelihood of splitting aisles between pallets (but may increase the expected number of pallets). pallet quantity).

Figure 11 shows the pallet load capacity for an order utilizing the package distribution method of the adjacent aisle planned pallet load described above. As mentioned above, the volume shown in Figure 11 corresponds to the volume of the walkway shown in Figure 5. According to the adjacent aisle pallet load parcel distribution method, a portion V2A of the volume V2 of aisle 2 consumes the entire/entire pallet load (e.g., pallet load 1), while the remaining volume V2B of aisle 2 considers pallets according to Figures 12 and 15 Plan (as mentioned above). Note that the volume V6 of aisle 6 is distributed between pallet loads 4 and 5, while the volume V12 of aisle 12 is distributed between pallet loads 6 and 7. The remaining volumes V1, V3, V4, V5 and V7-V11 of aisles 1, 3, 4, 5 and 7-11 and the remaining volume of aisle 2 are allocated only to a single corresponding pallet load, and each pallet load There is an uninterrupted sequence of aisles assigned to pallet loads. In this example, the total number of pallet loads is 7 (as shown in Figure 10, the pallet load plan is "pure" aisle adjacency, i.e., thresholds Vp0, Vp1 and double nested loops RL1, RL2 are not used) ; However, in Figure 11, the last pallet load (Pallet Load 7) is smaller in size compared to the last pallet load in Figure 10 and can be placed within the order of another pallet load top, thereby reducing the amount of floor space required to transport ordered pallet loads. It is important to note that often the "modified" adjacent aisle pallet load parcel allocation method (which allows the aisle bin unit volume to be split between pallet loads) results in a planned pallet load number that is less than "pure" adjacent Aisle pallet load parcel distribution method (split aisle box unit volume between pallet loads is not allowed).

Referring now to Figures 1-4 and 16, a method of establishing a pallet load PALO based on the clustered aisle pallet load parcel allocation method, the mixed mode cluster and adjacent aisle pallet load parcel allocation method, and the adjacent aisle pallet load parcel allocation method will be described. Any one or more of the plate load parcel distribution methods. Here, the package is placed on the pallet (see Figure 1) to form the pallet load PALO (Figure 16 block 1600). As described herein, a single case unit CU is provided from the storage array 130 to an automated stacker to form a pallet load PALO, wherein the pallet load PALO includes more than one composite layer L1 -Ln of the case unit CU. The pallet load PALO is composed of the container unit CU, which is arranged in the pallet load PALO, embodies at least one pallet affinity characteristic 166, 166' (block 1610 in Figure 16) for the ordering store, and is used to allocate pallets at the ordering store 200. Booking method for plate load packages. As described herein, at least one pallet to ordering store affinity feature 166, 166' is for a pallet load package distribution method at the ordering store, a pallet load package distribution method for cluster racking and adjacent racking, and adjacent racking The shelves are loaded with at least one method of dispensing packages in the order store.

According to one or more aspects of the present disclosure, a material handling system for handling and placing packages on pallets destined for ordering stores includes: a storage space for receiving the packages therein. a storage array; an automated package transfer system communicatively connected to the storage array, for storing the package in the storage space of the storage array and retrieving the package from the storage space of the storage array; for transporting the package An automatic palletizer placed onto a pallet to form a pallet load, the automatic palletizer communicatively connected to the automated package transfer system, the automated package transfer system configured to provide individual packages from the storage array to the an automatic stacker to form the pallet load, the pallet load including more than one layer of composite ply packages; and a controller operatively connected to the automatic stacker, the controller programmed to have the pallet load A generator, the pallet load generator having at least one pallet to ordering store affinity characteristic, a predetermined method for pallet load package distribution at the ordering store, the pallet load generator configured such that the pallet load is Formed by the automatic stacker that arranges the packages in the pallet load, the at least one pallet is characterized by ordering store affinity.

In accordance with one or more aspects of the present disclosure, the at least one pallet-to-subscribing store affinity feature is a clustered aisle pallet load package distribution method, mixed-mode clustered and adjacent aisle pallet loads at the subscribing store. at least one of a package distribution method, and an adjacent aisle pallet load package distribution method.

According to one or more aspects of the present disclosure, the at least one pallet-to-order store affinity property is informed by a repeating dual loop determination of at least one loop that associates order store aisles to one another.

According to one or more aspects of the present disclosure, within the determination of the at least one loop, ordering store aisles are related to each other by at least one of an aisle-to-aisle affinity property and a product group type to product group type affinity property.

According to one or more aspects of the present disclosure, the aisle-to-aisle affinity characteristic is the distance between one ordering store aisle and another ordering store aisle, or the continuity or adjacency of one ordering store aisle to another ordering store aisle. sex.

In accordance with one or more aspects of the present disclosure, the at least one pallet-to-ordering store affinity property is informed by a repeating dual-loop determination of at least one loop of determination that resolves the placement of packages in the pallet load. Available combinations for ordering store aisles.

According to one or more aspects of the present disclosure, each of the available combinations of ordering store aisles is determined based on maximizing the pallet load, or maximizing the combined pallet load and the available combinations. Continuity or adjacency of aisles where maximization of pallet loads is given a higher weight than continuity or adjacency of aisles.

According to one or more aspects of the present disclosure, each of the available combinations of order store aisles is based more on continuity or contiguity of the order store aisles in the available combinations and less on the pallet load. Maximize to determine.

According to one or more aspects of the present disclosure, each of the available combinations of order store aisles is based more on continuity or contiguity of the order store aisles in the available combinations and less on the pallet load. Maximize to determine.

According to one or more aspects of the present disclosure, the pallet load generator parses the pallet load based on the at least one pallet to ordering store affinity characteristics such that the pallet load has a load from a minimum number of ordering store aisles. Maximum number of packages.

According to one or more aspects of the present disclosure, the pallet load generator parses the pallet load based on the at least one pallet to ordering store affinity characteristics to generate a minimum number of pallet loads for each ordering store.

According to one or more aspects of the present disclosure, the pallet load generator parses the pallet load based on the at least one pallet to ordering store affinity characteristics such that for each pallet load destined for the ordering store, The packages that form this pallet load represent the minimum number of orders for a store aisle.

According to one or more aspects of the present disclosure, the pallet load generator parses the pallet load based on the at least one pallet to ordering store affinity characteristics such that for each pallet load destined for the ordering store, This resolved pallet load represents the minimum quantity to order a store aisle.

In accordance with one or more aspects of the present disclosure, the pallet load generator is configured to resolve each pallet load in sequence by informing the at least one pallet of repeated dual-loop determinations of ordering store affinity characteristics.

According to one or more aspects of the present disclosure, the at least one pallet-to-order store affinity property is informed by a dual-nested loop determination, at least one of which interconnects order-store aisles or Determine the available combinations of ordered store aisles that resolve the arrangement of packages in this pallet load.

According to one or more aspects of the present disclosure, an automatic stacker includes: an automatic package picking device capable of moving packages from a package storage portion to a pallet to form a pallet load from the package, the pallet load including more than one layer of composite ply packages; and a controller operatively connected to the automatic stacker, the controller programmed to have a pallet load generator having at least one pallet pair ordered Store affinity feature, a predetermined method for pallet load package distribution at the ordering store, the pallet load generator configured such that the pallet load is formed by the automatic stacker that arranges the packages in the pallet load , reflecting the affinity characteristic of the at least one pallet to the ordering store.

In accordance with one or more aspects of the present disclosure, the at least one pallet-to-subscribing store affinity feature is a clustered aisle pallet load package distribution method, mixed-mode clustered and adjacent aisle pallet loads at the subscribing store. at least one of a package distribution method, and an adjacent aisle pallet load package distribution method.

According to one or more aspects of the present disclosure, the at least one pallet-to-order store affinity property is informed by a repeating dual loop determination of at least one loop that associates order store aisles to one another.

According to one or more aspects of the present disclosure, within the determination of the at least one loop, ordering store aisles are related to each other by at least one of an aisle-to-aisle affinity property and a product group type to product group type affinity property.

According to one or more aspects of the present disclosure, the aisle-to-aisle affinity characteristic is the distance between one ordering store aisle and another ordering store aisle, or the continuity or adjacency of one ordering store aisle to another ordering store aisle. sex.

In accordance with one or more aspects of the present disclosure, the at least one pallet-to-ordering store affinity property is informed by a repeating dual-loop determination of at least one loop of determination that resolves the placement of packages in the pallet load. Available combinations for ordering store aisles.

According to one or more aspects of the present disclosure, each of the available combinations of ordering store aisles is determined based on maximizing the pallet load, or maximizing the combined pallet load and the available combinations. Continuity or adjacency of aisles where maximization of pallet loads is given a higher weight than continuity or adjacency of aisles.

According to one or more aspects of the present disclosure, each of the available combinations of order store aisles is based more on continuity or contiguity of the order store aisles in the available combinations and less on the pallet load. Maximize to determine.

According to one or more aspects of the present disclosure, the pallet load generator resolves the pallet load based on the at least one pallet to ordering store affinity characteristics such that the pallet load is relative to a maximum pallet load volume and a maximum At least one of the pallet load weights is maximized.

According to one or more aspects of the present disclosure, the pallet load generator parses the pallet load based on the at least one pallet to ordering store affinity characteristics such that the pallet load has a load from a minimum number of ordering store aisles. Maximum number of packages.

According to one or more aspects of the present disclosure, the pallet load generator parses the pallet load based on the at least one pallet to ordering store affinity characteristics to generate a minimum number of pallet loads for each ordering store.

According to one or more aspects of the present disclosure, the pallet load generator parses the pallet load based on the at least one pallet to ordering store affinity characteristics such that for each pallet load destined for the ordering store, The packages that form this pallet load represent the minimum number of orders for a store aisle.

According to one or more aspects of the present disclosure, the pallet load generator parses the pallet load based on the at least one pallet to ordering store affinity characteristics such that for each pallet load destined for the ordering store, This resolved pallet load represents the minimum quantity to order a store aisle.

In accordance with one or more aspects of the present disclosure, the pallet load generator is configured to resolve each pallet load in sequence by informing the at least one pallet of repeated dual-loop determinations of ordering store affinity characteristics.

According to one or more aspects of the present disclosure, the at least one pallet-to-order store affinity property is informed by a dual-nested loop determination, at least one of which interconnects order-store aisles or Determine the available combinations of ordered store aisles that resolve the arrangement of packages in this pallet load.

In accordance with one or more aspects of the present disclosure, a method of constructing a pallet load includes placing packages on a pallet to form the pallet load, wherein individual packages are provided from a storage array to form the pallet. a load, the pallet load comprising more than one composite layer of packages; and wherein the pallet load is formed from packages arranged within the pallet load, the pallet load embodying a pallet load of packages for use at the ordering store At least one pallet of the assigned booking method has an affinity property for the ordering store.

In accordance with one or more aspects of the present disclosure, the at least one pallet-to-subscribing store affinity feature is a clustered aisle pallet load package distribution method, mixed-mode clustered and adjacent aisle pallet loads at the subscribing store. at least one of a package distribution method, and an adjacent aisle pallet load package distribution method.

According to one or more aspects of the present disclosure, the at least one pallet-to-order store affinity property is informed by a repeating dual loop determination of at least one loop that associates order store aisles to one another.

According to one or more aspects of the present disclosure, within the determination of the at least one loop, ordering store aisles are related to each other by at least one of an aisle-to-aisle affinity property and a product group type to product group type affinity property.

According to one or more aspects of the present disclosure, the aisle-to-aisle affinity characteristic is the distance between one ordering store aisle and another ordering store aisle, or the continuity or adjacency of one ordering store aisle to another ordering store aisle. sex.

In accordance with one or more aspects of the present disclosure, the at least one pallet-to-ordering store affinity property is informed by a repeating dual-loop determination of at least one loop of determination that resolves the placement of packages in the pallet load. Available combinations for ordering store aisles.

According to one or more aspects of the present disclosure, each of the available combinations of ordering store aisles is determined based on maximizing the pallet load, or maximizing the combined pallet load and the available combinations. Continuity or adjacency of aisles where maximization of pallet loads is given a higher weight than continuity or adjacency of aisles.

According to one or more aspects of the present disclosure, each of the available combinations of order store aisles is based more on continuity or contiguity of the order store aisles in the available combinations and less on the pallet load. Maximize to determine.

According to one or more aspects of the present disclosure, the pallet load is parsed based on the affinity of the at least one pallet to the ordering store such that the pallet load is relative to a maximum pallet load volume and a maximum pallet load weight. of at least one maximization.

According to one or more aspects of the present disclosure, the pallet load is parsed based on the at least one pallet's ordering store affinity characteristics such that the pallet load has a maximum number of packages from a minimum number of ordering store aisles.

According to one or more aspects of the present disclosure, the pallet load is parsed based on the at least one pallet affinity to the ordering store to generate a minimum number of pallet loads for each ordering store.

According to one or more aspects of the present disclosure, the pallet load is parsed based on the affinity of the at least one pallet to the ordering store, such that for each pallet load sent to the ordering store, the pallet load is formed The packages represent the minimum quantity to order in store aisles.

According to one or more aspects of the present disclosure, the pallet load is parsed based on the affinity of the at least one pallet to the ordering store, such that for each pallet load sent to the ordering store, the parsed pallet Load represents the minimum quantity to order a store aisle.

In accordance with one or more aspects of the present disclosure, each pallet load is resolved sequentially through repeated dual-loop determinations of the at least one pallet's affinity to the ordering store.

According to one or more aspects of the present disclosure, the at least one pallet-to-order store affinity property is informed by a dual-nested loop determination, at least one of which interconnects order-store aisles or Determine the available combinations of ordered store aisles that resolve the arrangement of packages in this pallet load.

According to one or more aspects of the present disclosure, a pallet load includes: stacking more than one layer of composite layer packages on the pallet base; wherein the more than one layer of composite layer packages are arranged on the pallet Packages are formed in a load that embodies at least one pallet-to-order store affinity characteristic of a predetermined method for parcel distribution of the pallet load at the order store.

In accordance with one or more aspects of the present disclosure, the at least one pallet-to-subscribing store affinity feature is a clustered aisle pallet load package distribution method, mixed-mode clustered and adjacent aisle pallet loads at the subscribing store. at least one of a package distribution method, and an adjacent aisle pallet load package distribution method.

According to one or more aspects of the present disclosure, the at least one pallet-to-order store affinity property is informed by a repeating dual loop determination of at least one loop that associates order store aisles to one another.

According to one or more aspects of the present disclosure, within the determination of the at least one loop, ordering store aisles are related to each other by at least one of an aisle-to-aisle affinity property and a product group type to product group type affinity property.

According to one or more aspects of the present disclosure, the aisle-to-aisle affinity characteristic is the distance between one ordering store aisle and another ordering store aisle, or the continuity or adjacency of one ordering store aisle to another ordering store aisle. sex.

In accordance with one or more aspects of the present disclosure, the at least one pallet-to-ordering store affinity property is informed by a repeating dual-loop determination of at least one loop of determination that resolves the placement of packages in the pallet load. Available combinations for ordering store aisles.

According to one or more aspects of the present disclosure, each of the available combinations of ordering store aisles is determined based on maximizing the pallet load, or maximizing the combined pallet load and the available combinations. Continuity or adjacency of aisles where maximization of pallet loads is given a higher weight than continuity or adjacency of aisles.

According to one or more aspects of the present disclosure, each of the available combinations of order store aisles is based more on continuity or contiguity of the order store aisles in the available combinations and less on the pallet load. Maximize to determine.

According to one or more aspects of the present disclosure, the pallet load is parsed based on the affinity of the at least one pallet to the ordering store such that the pallet load is relative to a maximum pallet load volume and a maximum pallet load weight. of at least one maximization.

According to one or more aspects of the present disclosure, the pallet load is parsed based on the at least one pallet's ordering store affinity characteristics such that the pallet load has a maximum number of packages from a minimum number of ordering store aisles.

According to one or more aspects of the present disclosure, the pallet load is parsed based on the at least one pallet affinity to the ordering store to generate a minimum number of pallet loads for each ordering store.

According to one or more aspects of the present disclosure, the pallet load is parsed based on the affinity of the at least one pallet to the ordering store, such that for each pallet load sent to the ordering store, the pallet load is formed The packages represent the minimum quantity to order in store aisles.

According to one or more aspects of the present disclosure, the pallet load is parsed based on the affinity of the at least one pallet to the ordering store, such that for each pallet load sent to the ordering store, the parsed pallet Load represents the minimum quantity to order a store aisle.

In accordance with one or more aspects of the present disclosure, each pallet load is resolved sequentially through repeated dual-loop determinations of the at least one pallet's affinity to the ordering store.

According to one or more aspects of the present disclosure, the at least one pallet-to-order store affinity property is informed by a dual-nested loop determination, at least one of which interconnects order-store aisles or Determine the available combinations of ordered store aisles that resolve the arrangement of packages in this pallet load.

It should be understood that the foregoing description merely illustrates aspects of the present disclosure. Various substitutions and modifications may be devised by those skilled in the art without departing from the scope of the present disclosure. Accordingly, this disclosure is intended to include all such alternatives, modifications, and differences that fall within the scope of any claims appended hereto. Furthermore, the mere fact that different features are recited in mutually different dependent or independent claims does not indicate that a combination of these features cannot be used to advantage, which combinations still fall within the scope of this aspect of the disclosure.

199:Warehouse/Distribution Center 190:Material handling system 130:Storage array 130S:Storage space 130L: storage layer 130L1-130Ln: storage layer 130A: Picking aisle 130B:Transport deck 110: Autonomous transport vehicles/robots 140: Robot/Robot Transfer Station 195: Automated parcel delivery system 1220:Onboard processor/controller 150A, 150B: lifting module 160: Discharge transfer station 170: Feed transfer station 162:Stacker 162’:Depalletizer 162D: Automatic parcel picking device 164,164’:Controller 165,165’: pallet load generator 166,166’: The pallet is order-store friendly. 120:Control server 180: Communications and Control Networks/Networks 2500:Warehouse Management System CU: cargo container unit PALO: pallet load PALN: pallet load 222: Loading dock area 299:Mixed product order 200:Order store 233: Store shelves 224:Shopping area 300,301,302:Travel path PALOA,PALOA’: pallet load PALOC,PALOC’: pallet load PALO21, PALO22, PALO23: secondary pallet load PA: pallet-aisle binary matrix 700A,700B,710,720,730,735,740,745,750,755,760,765,770: Block 800:Example store order 1200,1210,1220,1230,1240,1250,1260: block 1330:Block 1430:Block 1500,1505,1510,1515,1520,1530,1535,1536,1540,1545,1550,1555,1560,1565,1570,1575,1580,1585,1590: Block 1600,1610: block

The foregoing aspects and other features of the present disclosure are explained in the following description in conjunction with the accompanying drawings, wherein:

[Fig. 1] is an exemplary schematic diagram of a warehouse or distribution center incorporating aspects of the present disclosure;

[Fig. 2] is an exemplary schematic diagram of pallet load package distribution according to aspects of the present disclosure;

[Fig. 3] is an exemplary schematic diagram of pallet load package distribution according to aspects of the present disclosure;

[Fig. 4] is an exemplary schematic diagram of pallet load package distribution according to aspects of the present disclosure;

[Fig. 5] is an exemplary schematic diagram of an order for pallet planning according to aspects of the present disclosure;

[Fig. 6] is an exemplary schematic diagram of a pallet-aisle binary matrix according to aspects of the present disclosure;

[Fig. 7] is an exemplary method according to aspects of the present disclosure;

[Fig. 8] is an exemplary schematic diagram of a planned order according to aspects of the present disclosure;

[Fig. 9] is an exemplary schematic diagram of the process of selecting pallets to aisles according to aspects of the present disclosure;

[Fig. 10] is an exemplary schematic diagram of container unit distribution of pallet loads according to aspects of the present disclosure;

[Fig. 11] is an exemplary schematic diagram of container unit distribution of pallet loads according to aspects of the present disclosure;

[Figures 12A and 12B] are illustrations of exemplary methods in accordance with aspects of the present disclosure;

[Fig. 13] is an illustration of an exemplary method according to aspects of the present disclosure;

[FIG. 14] is an illustration of an exemplary method according to aspects of the present disclosure;

[Fig. 15] is an illustration of an exemplary method according to aspects of the present disclosure;

[FIG. 16] is an illustration of an exemplary method in accordance with aspects of the present disclosure; and

[Fig. 17] is a graph illustrating changes in container dimensions among a representative group of containers.

200:Order store

233: Store shelves

299:Mixed product order

PALO21, PALO22, PALO23: secondary pallet load

PALOC,PALOC’: pallet load

Claims (60)

A material handling system for handling and placing packages onto pallets destined for ordering stores, including: a storage array having storage space for receiving packages therein; an automated package transfer system communicatively connected to the storage array for storing packages in the storage space of the storage array and retrieving the packages from the storage space of the storage array; An automated stacker for placing packages onto pallets to form pallet loads, the automated stacker being communicatively connected to the automated package transfer system configured to transfer individual packages from the storage Arrays are provided to the automated stacker to form the pallet load, the pallet load including more than one composite layer package; and A controller operably connected to the automated stacker, the controller programmed to have a pallet load generator having at least one pallet pair ordering store affinity feature for use in the ordering A predetermined method of pallet load package distribution for a store, the pallet load generator configured such that the pallet load is formed by the automatic stacker placing the packages in the pallet load, embodying the at least one pallet pair ordering Store affinity features. The material handling system of claim 1, wherein the at least one pallet pair ordering store affinity characteristic is a clustered aisle pallet load package distribution method, mixed mode cluster and adjacent aisle pallet loading at the ordering store at least one of a package distribution method, and an adjacent aisle pallet load package distribution method. The material handling system of claim 1, wherein the at least one pallet-to-order store affinity characteristic is informed by a repeating double loop determination that associates order store aisles with each other. The material handling system of claim 3, wherein within determination of the at least one loop, ordering store aisles are related to each other by at least one of an aisle-to-aisle affinity property and a product group type to product group type affinity property. The material handling system of claim 4, wherein the aisle-to-aisle affinity characteristic is the distance between one ordering store aisle and another ordering store aisle, or the continuity or adjacency of one ordering store aisle to another ordering store aisle. sex. The material handling system of claim 1, wherein the at least one pallet-to-order store affinity property is informed by a repeating double-loop determination of at least one loop of determination that resolves the arrangement of packages in the pallet load Available combinations for ordering store aisles. The material handling system of claim 6, wherein each of the available combinations of ordering store aisles is determined based on: Maximize the pallet load, or maximizing the combination of pallet loads and the continuity or contiguity of aisles in that available combination, The maximization of the pallet load is given a higher weight than the continuity or contiguity of the walkway. The material handling system of claim 6, wherein each of the available combinations of ordering store aisles is based more on continuity or contiguity of ordering store aisles in the available combinations and less on the pallet load Maximize to determine. The material handling system according to claim 1, wherein the pallet load generator parses the pallet load according to the at least one pallet to ordering store affinity characteristics, such that the pallet load is relative to the maximum pallet load volume and the maximum At least one of the pallet load weights is maximized. The material handling system of claim 1, wherein the pallet load generator parses the pallet load according to the at least one pallet to ordering store affinity characteristics such that the pallet load comes from a minimum number of ordering store aisles with a maximum Quantity of packages. The material handling system of claim 1, wherein the pallet load generator parses the pallet load according to the at least one pallet to ordering store affinity characteristics to generate a minimum number of pallet loads for each ordering store. The material handling system of claim 1, wherein the pallet load generator parses the pallet load according to the at least one pallet to ordering store affinity characteristics, such that for each pallet load sent to the ordering store, The packages that form this pallet load represent the minimum number of orders for a store aisle. The material handling system of claim 1, wherein the pallet load generator parses the pallet load according to the at least one pallet to ordering store affinity characteristics, such that for each pallet load sent to the ordering store, This resolved pallet load represents the minimum number of ordered store aisles. The material handling system of claim 1, wherein the pallet load generator is configured to resolve each pallet load in sequence by notifying the at least one pallet of repeated dual-loop determinations of affinity characteristics for the ordering store. The material handling system of claim 1, wherein the at least one pallet to ordering store affinity characteristic is informed by a dual nested loop determination, at least one of the dual nested loop determinations interrelating ordering store aisles or Determine the available combinations of ordered store aisles that resolve the arrangement of packages in this pallet load. An automatic stacker including: An automated package picking device capable of moving packages from a package storage unit to a pallet to form a pallet load from the package, the pallet load including more than one composite layer package; and A controller operably connected to the automated stacker, the controller programmed to have a pallet load generator having at least one pallet pair ordering store affinity feature for use in the ordering A predetermined method of pallet load package distribution for a store, the pallet load generator configured such that the pallet load is formed by the automatic stacker placing the packages in the pallet load, embodying the at least one pallet pair ordering Store affinity features. The automatic stacker of claim 16, wherein the at least one pallet to ordering store affinity characteristic is a clustered aisle pallet load package distribution method, mixed mode cluster and adjacent aisle pallets at the ordering store At least one of a load package distribution method, and an adjacent aisle pallet load package distribution method. The automatic stacker of claim 16, wherein the at least one pallet to ordering store affinity characteristic is informed by a repeating double loop determination of at least one loop of the repeating dual loop determination associating ordering store aisles with each other. The automatic stacker of claim 18, wherein within determination of the at least one loop, ordering store aisles are related to each other by at least one of an aisle-to-aisle affinity characteristic and a product group type to product group type affinity characteristic. The automatic stacker of claim 19, wherein the aisle-to-aisle affinity characteristic is the distance between one ordering store aisle and another ordering store aisle, or the continuity of one ordering store aisle to another ordering store aisle, or Contiguity. The automatic stacker of claim 16, wherein the at least one pallet-to-ordering store affinity characteristic is informed by a repeating dual-loop determination of at least one loop of the repeating dual-loop determination that resolves the package in the pallet load Available combinations of arranged ordering store aisles. The automatic stacker of claim 21, wherein each of the available combinations of ordering store aisles is determined based on: Maximize the pallet load, or maximizing the combination of pallet loads and the continuity or contiguity of aisles in that available combination, The maximization of the pallet load is given a higher weight than the continuity or contiguity of the walkway. The automatic stacker of claim 21, wherein each of the available combinations of order store aisles is based more on the continuity or contiguity of the order store aisles in the available combinations and less on the pallet load determined by maximizing. The automatic stacker of claim 16, wherein the pallet load generator parses the pallet load according to the at least one pallet to ordering store affinity characteristics, such that the pallet load is relative to the maximum pallet load volume and At least one of the maximum pallet load weights is maximized. The automatic stacker of claim 16, wherein the pallet load generator parses the pallet load based on the at least one pallet pair ordering store affinity characteristic such that the pallet load has a minimum number of ordering store aisles from The maximum number of packages. The automatic stacker of claim 16, wherein the pallet load generator parses the pallet load according to the at least one pallet to ordering store affinity characteristics to generate a minimum number of pallet loads for each ordering store. . The automatic stacker of claim 16, wherein the pallet load generator parses the pallet load according to the at least one pallet to ordering store affinity characteristics, such that for each pallet load sent to the ordering store , the packages that form this pallet load represent the minimum quantity ordered for the store aisle. The automatic stacker of claim 16, wherein the pallet load generator parses the pallet load according to the at least one pallet to ordering store affinity characteristics, such that for each pallet load sent to the ordering store , this resolved pallet load represents the minimum quantity to order a store aisle. The automatic stacker of claim 16, wherein the pallet load generator is configured to resolve each pallet load sequentially by notifying the at least one pallet of repeated dual-loop determinations of affinity characteristics for the ordering store. The automatic stacker of claim 16, wherein the at least one pallet to ordering store affinity characteristic is informed by a dual nested loop determination, at least one of the dual nested loop determinations interrelating ordering store aisles Or determine the available combinations of ordered store aisles that resolve the arrangement of packages in that pallet load. A method of constructing pallet loads, the method comprising: placing packages on pallets to form a pallet load, wherein individual packages are provided from a storage array to form the pallet load, the pallet load including packages of more than one composite layer; and Where the pallet load is formed from packages arranged in the pallet load, the pallet load embodies at least one pallet-to-ordering store affinity characteristic of a predetermined method for pallet load package distribution at the ordering store. The method of claim 31, wherein the at least one pallet pair ordering store affinity characteristic is a clustered aisle pallet load package distribution method, mixed mode cluster and adjacent aisle pallet load package distribution at the ordering store method, and at least one of adjacent aisle pallet load parcel distribution methods. The method of claim 31, wherein the at least one pallet-to-order store affinity property is informed by a repeating double loop determination of at least one loop that associates order store aisles with one another. The method of claim 33, wherein within the determination of the at least one loop, ordering store aisles are related to each other by at least one of an aisle-to-aisle affinity property and a product group type to product group type affinity property. The method of claim 34, wherein the aisle-to-aisle affinity characteristic is the distance between one ordering store aisle and another ordering store aisle, or the continuity or contiguity of one ordering store aisle to another ordering store aisle. The method of claim 31, wherein the at least one pallet-to-ordering store affinity property is informed by a repeating double-loop determination of at least one loop of determination that resolves an ordering arrangement for packages in the pallet load Available combinations for store aisles. The method of claim 36, wherein each of the available combinations of ordering store aisles is determined based on: Maximize the pallet load, or maximizing the combination of pallet loads and the continuity or contiguity of aisles in that available combination, The maximization of the pallet load is given a higher weight than the continuity or contiguity of the walkway. The method of claim 36, wherein each of the available combinations of order store aisles is based more on continuity or contiguity of order store aisles in the available combinations and less on maximization of the pallet load to be sure. The method of claim 31, wherein the pallet load is parsed based on the at least one pallet pair ordering store affinity characteristic such that the pallet load is relative to at least one of a maximum pallet load volume and a maximum pallet load weight. A maximization. The method of claim 31, wherein the pallet load is parsed based on the at least one pallet to order store affinity properties such that the pallet load has a maximum number of packages from a minimum number of order store aisles. The method of claim 31, wherein the pallet load is parsed based on the at least one pallet to ordering store affinity characteristics to generate a minimum number of pallet loads for each ordering store. The method of claim 31, wherein the pallet load is parsed based on the at least one pallet to ordering store affinity properties such that for each pallet load sent to the ordering store, a package of the pallet load is formed Represents minimum quantity for ordering store aisles. The method of claim 31, wherein the pallet load is parsed based on the at least one pallet pair ordering store affinity property such that for each pallet load sent to the ordering store, the parsed pallet load represents Minimum quantity for ordering store aisles. 31. The method of claim 31, wherein each pallet load is parsed sequentially by repeating double-loop determinations of the at least one pallet's affinity to the ordering store. The method of claim 31, wherein the at least one pallet-to-order store affinity property is informed by a dual-nested loop determination, at least one of the dual-nested loop determinations interrelating or determining parsing of order store aisles. The arrangement of packages in this pallet load is ordered from the available combinations of store aisles. A pallet load consisting of: Packages stacking more than one composite layer on a pallet base; wherein the packages of more than one composite layer are formed from packages arranged in the pallet load, the pallet load embodying a predetermined method for distribution of the pallet load packages at the ordering store with at least one pallet having an affinity for the ordering store characteristic. The pallet load of claim 46, wherein the at least one pallet pair ordering store affinity characteristic is a clustered aisle pallet load package allocation method, mixed mode cluster and adjacent aisle pallet loading at the ordering store at least one of a package distribution method, and an adjacent aisle pallet load package distribution method. The pallet load of claim 46, wherein the at least one pallet-to-order store affinity characteristic is informed by a repeating dual loop determination of at least one loop of the repeating dual loop determination that associates order store aisles to one another. The pallet load of claim 48, wherein within determination of the at least one circuit, ordering store aisles are related to each other by at least one of an aisle-to-aisle affinity characteristic and a product group type to product group type affinity characteristic. The pallet load of claim 49, wherein the aisle-to-aisle affinity characteristic is the distance between one order store aisle and another order store aisle, or the continuity or adjacency of one order store aisle to another order store aisle. sex. The pallet load of claim 46, wherein the at least one pallet-to-ordering store affinity property is informed by a repeating dual-loop determination of at least one loop of the repeating dual-loop determination that resolves a placement of packages in the pallet load Available combinations for ordering store aisles. The pallet load of claim 51, wherein each of the available combinations of ordering store aisles is determined based on: Maximize the pallet load, or maximizing the combination of pallet loads and the continuity or contiguity of aisles in that available combination, The maximization of the pallet load is given a higher weight than the continuity or contiguity of the walkway. The pallet load of claim 51, wherein each of the available combinations of order store aisles is based more on continuity or contiguity of the order store aisles in the available combinations and less on the pallet load Maximize to determine. The pallet load of claim 46, wherein the pallet load is resolved based on the at least one pallet pair ordering store affinity property such that the pallet load is relative to a maximum pallet load volume and a maximum pallet load weight. of at least one maximization. The pallet load of claim 46, wherein the pallet load is parsed based on the at least one pallet to order store affinity properties such that the pallet load has a maximum number of packages from a minimum number of order store aisles. The pallet load of claim 46, wherein the pallet load is parsed based on the at least one pallet to ordering store affinity property to generate a minimum number of pallet loads for each ordering store. The pallet load of claim 46, wherein the pallet load is parsed based on the at least one pallet to ordering store affinity property such that for each pallet load sent to the ordering store, the pallet load is formed The packages represent the minimum quantity to order in store aisles. The pallet load of claim 46, wherein the pallet load is parsed based on the at least one pallet to ordering store affinity property such that for each pallet load sent to the ordering store, the parsed pallet Load represents the minimum quantity to order a store aisle. The pallet load of claim 46, wherein each pallet load is parsed sequentially by repeating double-loop determinations of the at least one pallet's affinity to the ordering store. The pallet load of claim 46, wherein the at least one pallet-to-order store affinity characteristic is informed by a dual-nested loop determination, at least one of the dual-nested loop determinations interconnecting order-store aisles, or Determine the available combinations of ordered store aisles that resolve the arrangement of packages in this pallet load.

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