CN112036635A - Order aggregation method and system for shortening warehouse goods distribution walking path - Google Patents
Order aggregation method and system for shortening warehouse goods distribution walking path Download PDFInfo
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- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
- G06Q10/0835—Relationships between shipper or supplier and carriers
- G06Q10/08355—Routing methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
- G06Q10/0836—Recipient pick-ups
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
- G06Q10/0875—Itemisation or classification of parts, supplies or services, e.g. bill of materials
Abstract
The invention discloses an order aggregation method and system for shortening a warehouse goods distribution walking path, which can shorten the walking path length required by picking all orders and improve the warehouse goods distribution working efficiency. The technical scheme is as follows: data abstraction and definition are carried out on the order according to the order picking sequence of the storage positions corresponding to the commodities in the order detail, and the problem of the picking path length is converted into the problem of the distance between the midpoint and the point in the two-dimensional space on the basis of the order definition, so that the complex problem of batch path aggregation optimization is converted into a simple problem of clustering the two-dimensional space points, and the technical effect of rapidly calculating the optimization result is achieved. Compared with the prior art, the invention realizes the technical effect of shortening the length of the goods picking walking path of the warehouse, thereby improving the work efficiency of goods distribution of the warehouse.
Description
Technical Field
The invention relates to an order distribution and picking link of an e-commerce warehouse, in particular to an order aggregation method and system for shortening a warehouse distribution walking path.
Background
Currently, more and more e-commerce warehouses using WMS management software use order picking trucks for order distribution, typically one picking truck carries several picking baskets, each of which can carry 1 order (in some cases, one picking basket may also carry multiple orders). Thus, a pick-up truck typically carries several orders, the collection of orders in the truck, which we generally refer to as a pick-up lot (referred to as a "lot").
The use of pick trucks increases the loading capacity of the order taker per pick walk, but also presents a new problem: different orders need to be picked from shelves in different positions, and a lot with poor aggregation can greatly prolong the walking distance of a goods distributor pulling a picking truck in the warehouse. For example, 10 orders in a batch, 8 of which can be picked in the first 3 lanes, but the remaining 2 orders have more goods and need to go further 15 lanes to complete the order, which results in a greatly prolonged picking workload for completing the first 8 orders.
Some WMS systems also recognize this problem and attempt to solve it either systematically or manually. For example, when aggregating orders, the order of the goods picked earliest in the order is used as an index for aggregation; as another example, in creating a batch generation rule, the order required for a pick lane is defined, trying to group together orders that can all be completed in the first 3 lanes.
However, these solutions are rough and unsatisfactory in terms of solution effect, and include the following disadvantages:
1. only the initial part of the order is aggregated, the length of the order cannot be effectively controlled, and a plurality of small orders still run on the whole field along with a large order;
2. the manual channel limitation during batch configuration has a certain control on the batch length, but only a few rules can be configured in actual operation. Firstly, to achieve the purpose that a large number of rules need to be configured, for example, if a certain warehouse has N channels, N (N-1)/2 rules such as only 1 channel, only 1-2 channel, only 2 channel … … and the like need to be configured, the workload is huge, and the actual operation is almost impossible; secondly, the order aggregation is difficult to be done when the division is too fine due to the fact that the order aggregation is relatively rigid. Therefore, reasonable order aggregation is difficult to achieve in this way;
3. these lack a flexible order aggregation mode, and further cause a channel congestion problem after aggregation, which reduces the distribution efficiency.
Disclosure of Invention
The following presents a simplified summary of one or more aspects in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements of all aspects nor delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later.
The present invention is directed to solve the above problems, and provides an order aggregation method and system for shortening a warehouse distribution travel path, which aggregates orders with high similarity on a picking path into a same batch, and allows the picking path required to travel to complete the batch to be close to a path required by any order in the batch, thereby shortening the travel path length required to complete all orders and improving the warehouse distribution work efficiency.
The technical scheme of the invention is as follows: the invention discloses an order aggregation method for shortening a warehouse distribution walking path, which comprises the following steps:
the method comprises the following steps: binding the shelf walking index of each storage position;
step two: carrying out initialization processing on the order;
step three: determining a two-dimensional coordinate point of the order in a two-dimensional coordinate system according to the commodity content of the order, wherein the walking index value of the initial goods shelf of each order is an abscissa, and the walking index value of the final goods shelf is an ordinate;
step four: aggregating all orders into a plurality of batches according to the coordinate distances between the two-dimensional coordinate points corresponding to all orders and the stock, wherein the orders with the close coordinate distances are aggregated into the same batch, and the orders with insufficient stock are removed from an order pool;
step five: before generating the batches, sequencing the aggregated batches so that a plurality of adjacent batches cannot be picked from the same channel;
step six: outputting the generated order batch.
According to an embodiment of the order aggregation method for shortening the warehouse distribution walking path, the order initialization processing in the second step comprises primary screening and classification of orders, wherein the screening comprises removing orders which cannot meet the requirements of goods in stock, the classification comprises classification according to the order volumes, different types of orders are distributed to different order pools, only orders in the same order pool can be aggregated, and orders in different order pools cannot be aggregated.
According to an embodiment of the order aggregation method for shortening the warehouse distribution walking path, the step four further includes:
step 4-1: path aggregation is carried out on any order pool;
step 4-2: selecting any order in the order pool as a batch first order, and carrying out inventory verification on the order;
step 4-3: judging whether the inventory meets the requirements of all commodities in the order in the inventory verification, if so, entering a step 4-4, and if not, entering a step 4-14; .
Step 4-4: taking the order into a batch as a batch primary order, and deducting corresponding commodity inventory;
and 4-5: calculating the square of the Euclidean distance from all other orders in the order pool to the order;
and 4-6: sorting according to the Euclidean distance from other orders to the first order of the batch from small to large;
and 4-7: taking out the order which is closest to the customer and is not taken into the batch or is not removed, and carrying out inventory check on the order;
and 4-8: judging whether the inventory meets all commodity requirements of the order in inventory verification, if so, switching to a step 4-9, and if not, switching to a step 4-13;
and 4-9: bringing the order into a batch and deducting corresponding commodity inventory;
step 4-10: judging whether the batch is full of orders of the whole batch, if so, switching to the step 4-11, otherwise, switching to the step 4-13;
and 4-11: judging whether all orders in the order pool are aggregated into a batch, if so, switching to the step 4-12, otherwise, returning to the step 4-2;
and 4-12: finishing the batch polymerization;
step 4-13: removing the order from the order pool, reselecting the order, and then switching to the step 4-7;
and 4-14: the order is removed from the order pool and the order is reselected, and then step 4-2 is carried out.
The invention also discloses an order aggregation system for shortening the warehouse distribution walking path, which comprises:
the binding module is used for binding the shelf walking index of each storage position;
the order initialization module is used for initializing orders;
the two-dimensional coordinate mapping module is used for determining two-dimensional coordinate points of the orders in a two-dimensional coordinate system according to the commodity contents of the orders, wherein the walking index value of the initial goods shelf of each order is an abscissa, and the walking index value of the final goods shelf is an ordinate;
the batch aggregation module aggregates all orders into a plurality of batches according to the coordinate distances between the two-dimensional coordinate points corresponding to all orders and the inventory, wherein the orders with the close coordinate distances are aggregated into the same batch, and the orders with insufficient inventory are removed from an order pool;
the sorting module sorts the aggregated batches before generating the batches so that a plurality of adjacent batches cannot be picked from the same channel;
and the order batch output module outputs the generated order batch.
According to an embodiment of the order aggregation system for shortening the warehouse distribution walking path, the order initialization module is further configured to perform preliminary screening and classification on the orders, wherein the screening includes removing orders whose stock cannot meet the demand of the goods, the classification includes classifying according to the order volumes, different types of orders are allocated to different order pools, only orders in the same order pool can be aggregated, and orders in different order pools cannot be aggregated.
According to an embodiment of the order aggregation system for shortening the warehouse distribution walking path of the present invention, the batch aggregation module is further configured to perform the following processes:
step 4-1: path aggregation is carried out on any order pool;
step 4-2: selecting any order in the order pool as a batch first order, and carrying out inventory verification on the order;
step 4-3: judging whether the inventory meets the requirements of all commodities in the order in the inventory verification, if so, entering a step 4-4, and if not, entering a step 4-14; .
Step 4-4: taking the order into a batch as a batch primary order, and deducting corresponding commodity inventory;
and 4-5: calculating the square of the Euclidean distance from all other orders in the order pool to the order;
and 4-6: sorting according to the Euclidean distance from other orders to the first order of the batch from small to large;
and 4-7: taking out the order which is closest to the customer and is not taken into the batch or is not removed, and carrying out inventory check on the order;
and 4-8: judging whether the inventory meets all commodity requirements of the order in inventory verification, if so, switching to a step 4-9, and if not, switching to a step 4-13;
and 4-9: bringing the order into a batch and deducting corresponding commodity inventory;
step 4-10: judging whether the batch is full of orders of the whole batch, if so, switching to the step 4-11, otherwise, switching to the step 4-13;
and 4-11: judging whether all orders in the order pool are aggregated into a batch, if so, switching to the step 4-12, otherwise, returning to the step 4-2;
and 4-12: finishing the batch polymerization;
step 4-13: removing the order from the order pool, reselecting the order, and then switching to the step 4-7;
and 4-14: the order is removed from the order pool and the order is reselected, and then step 4-2 is carried out.
The invention also discloses an order aggregation system for shortening the warehouse distribution walking path, which comprises:
a processor; and
a memory configured to store a series of computer-executable instructions and computer-accessible data associated with the series of computer-executable instructions,
wherein the series of computer executable instructions, when executed by the processor, cause the processor to perform the method as described above.
The present invention additionally discloses a non-transitory computer readable storage medium having stored thereon a series of computer executable instructions which, when executed by a computing device, cause the computing device to perform the method as described above.
Compared with the prior art, the invention has the following beneficial effects: the scheme of the invention is that data abstraction and definition are carried out on an order according to the order picking sequence of the corresponding storage position of each commodity in the order detail, and the problem of the length of the picking path is converted into the problem of the point-to-point distance in a two-dimensional space on the basis of the order definition, so that the complex problem of batch path aggregation optimization is converted into a simple problem of clustering the two-dimensional space points, and the technical effect of rapidly calculating the optimization result is achieved. Compared with the prior art, the invention realizes the technical effect of shortening the length of the goods picking walking path of the warehouse, thereby improving the work efficiency of goods distribution of the warehouse.
Drawings
The above features and advantages of the present disclosure will be better understood upon reading the detailed description of embodiments of the disclosure in conjunction with the following drawings. In the drawings, components are not necessarily drawn to scale, and components having similar relative characteristics or features may have the same or similar reference numerals.
Fig. 1 and 2 show exemplary diagrams of the principle on which the order aggregation method for shortening the warehouse pick-up travel path of the present invention is based.
Fig. 3 is a flow chart illustrating an embodiment of an order aggregation method for shortening a warehouse pick-up travel path according to the present invention.
Fig. 4 shows a block diagram of an embodiment of the order aggregation system for shortening the warehouse distribution travel path of the present invention.
Fig. 5 is a block diagram illustrating another embodiment of an order aggregation system for shortening a warehouse distribution travel path according to the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. It is noted that the aspects described below in connection with the figures and the specific embodiments are only exemplary and should not be construed as imposing any limitation on the scope of the present invention.
Before describing the solution of an embodiment of the order aggregation method for shortening the warehouse pick-up walking path of the present invention, the principle on which this method is based is first illustrated by way of an example.
For a particular warehouse, most of the shelves are relatively fixed, so that when the aggregation degree of the order paths is good enough, the length of the walking path required for completing a certain order is considered to be in direct proportion to the number of shelves passed by the order. Meanwhile, since the order aggregation is good enough, when the batch of the order is completed, the route channel has the picking operation, and the jumping or short-cut of the channel or the area cannot be carried out. Therefore, we can locate an order in the one-dimensional coordinate system with the rack walking index (the "rack walking index" is an important parameter related to the rack sequence, and may also be referred to as "rack walking index" hereinafter), where the racks in the general warehouse all have rack numbers, and the order allocator will generally continue picking according to a certain rack sequence according to the difference of the system setting on the rack numbers, and unlike the rack number, the rack walking index is the picking sequence code of the full-warehouse rack, and generally increases one by one in integer units from 1, and the maximum rack walking index is generally equal to the total rack number in the warehouse), as shown in fig. 1:
the goods shelf where the goods picked first in the order A are located is a1(where a)11), the goods shelf where the goods picked up last is a2(where a)25) to complete the order, a is taken2-a1A number of shelves (here 4 shelves); similarly, we can also pass through the starting shelf b1And terminating shelf b2Position order B, start shelf c1And terminating shelf c2Order C is located. Is easy to see although b1≠c1And b is2≠c2However, order B and order C are more suitable for aggregation.
Further, we establish a two-dimensional coordinate system with the start rack index as the X-axis and the end rack index as the Y-axis, and locate A, B, C orders above as shown in fig. 2:
as can be seen most clearly in fig. 2, in this two-dimensional coordinate system, orders that are close together are more suitable to be aggregated in a batch, i.e. by determining the euclidean distance between two orders:
the degree of the two orders can be determined, and the smaller the distance, the more suitable the polymerization, and the larger the distance, the less suitable the polymerization.
Fig. 3 shows a flow of an embodiment of an order aggregation method for shortening a warehouse pick-up travel path according to the present invention. Referring to fig. 3, the implementation of each step in the method of the present embodiment is described in detail as follows.
The method comprises the following steps: and binding the shelf walking index of each storage position.
Each library position is designed with a library position code: the library bit code is typically in the format of "A04-03-05-02", for example, the number of specific numbering bits varies according to the warehouse, the first bit (e.g., A04) is typically a region or channel code, the first two (e.g., A04-03) are shelf codes, and the last two (e.g., 05-02) are the layer number (5 layers) and the column number (2 nd library bit) on the same shelf.
The storage position code is only one identification number of the storage position and does not represent the sequence of the shelf walking indexes. The merchant will typically plan a pick route based on the warehouse field layout and the route, and the shelf walking index is derived from the order of a shelf in the merchant's planned field pick route.
Step two: and carrying out initialization processing on the order.
The order initialization process in this step includes preliminary screening and sorting of orders. For example, orders whose stock can not meet the demand of goods are rejected (currently, the order can not be completed, and the order can be allocated next time after the replenishment is in place), and then sorted according to the order volume so as to be allocated to pick-up trucks with the size meeting the demand. Orders are typically categorized into categories 2-4, with orders of different categories being assigned to different order pools for loading into different order trucks. Only orders from the same order pool can be aggregated, and orders from different order pools cannot be aggregated, otherwise the pick-up truck may not be loaded or may be loaded too little.
Step three: determining the coordinates (X, Y) of the order in a two-dimensional coordinate system according to the order commodity content: the start shelf index value of each order is the abscissa X and the end shelf index value is the ordinate Y.
Step four: aggregating all orders into several batches according to coordinate distance and inventory: orders with close coordinate distances are aggregated into the same batch, and orders with insufficient inventory are culled out of the order pool.
The concrete implementation steps of the fourth step are as follows:
step 4-1: path aggregation is performed on any order pool.
Step 4-2: any order in the order pool is selected as a batch first order, and inventory verification is carried out on the order.
Step 4-3: and judging whether the inventory meets the requirements of all the commodities in the order in the inventory verification, if so, entering a step 4-4, and otherwise, entering a step 4-14.
Step 4-4: the order is taken into the batch and taken as the first order of the batch, and the corresponding inventory of the goods is deducted.
And 4-5: the square of the Euclidean distance to the order is calculated for all other orders in the order pool.
And 4-6: and sorting according to the Euclidean distance from other orders to the first order of the batch from small to large.
And 4-7: the order which is closest to the customer and not included in the batch or not removed is taken and subjected to inventory verification.
And 4-8: and judging whether the inventory meets all commodity requirements of the order in inventory verification, if so, switching to a step 4-9, and if not, switching to a step 4-13.
And 4-9: the order is taken into the batch and the corresponding inventory of goods is deducted.
Step 4-10: and judging whether the batch is full of orders of the whole batch, if so, switching to the step 4-11, and otherwise, switching to the step 4-13.
And 4-11: and judging whether all orders in the order pool are aggregated into a batch, if so, switching to the step 4-12, and otherwise, returning to the step 4-2.
And 4-12: and finishing the batch polymerization.
Step 4-13: the order is removed from the order pool and the order is reselected, and then step 4-7 is carried out.
And 4-14: the order is removed from the order pool and the order is reselected, and then step 4-2 is carried out.
Step five: in order to prevent the situation of channel congestion, before the batches are generated, the aggregated batches are sorted, so that a plurality of adjacent batches cannot be picked from the same channel.
Step six: outputting the generated order batch.
Fig. 4 shows the structure of an embodiment of the order aggregation system for shortening the warehouse pick-up travel path of the present invention. Referring to fig. 4, the system diagram of the present embodiment includes: the system comprises a binding module, an order initialization module, a two-dimensional coordinate mapping module, a batch aggregation module, a sorting module and an order batch output module.
The binding module is used for binding the shelf walking index of each storage position.
Each library position is designed with a library position code: the library bit code is typically in the format of "A04-03-05-02", for example, the number of specific numbering bits varies according to the warehouse, the first bit (e.g., A04) is typically a region or channel code, the first two (e.g., A04-03) are shelf codes, and the last two (e.g., 05-02) are the layer number (5 layers) and the column number (2 nd library bit) on the same shelf.
The storage position code is only one identification number of the storage position and does not represent the sequence of the shelf walking indexes. The merchant will typically plan a pick route based on the warehouse field layout and the route, and the shelf walking index is derived from the order of a shelf in the merchant's planned field pick route.
The order initialization module is used for initializing orders. The order initialization module is further configured to perform preliminary screening and sorting on the orders, wherein the screening includes removing orders whose stock cannot meet the demand of the goods, the sorting includes sorting according to the order volume, different types of orders are distributed to different order pools, only orders in the same order pool can be aggregated, and orders in different order pools cannot be aggregated.
The two-dimensional coordinate mapping module is used for determining a two-dimensional coordinate point of each order in the two-dimensional coordinate system according to the commodity content of the order, wherein the walking index value of the starting shelf of each order is an abscissa, and the walking index value of the ending shelf is an ordinate.
The batch aggregation module is used for aggregating all orders into a plurality of batches according to the coordinate distances between the two-dimensional coordinate points corresponding to all the orders and the inventory, wherein the orders with the close coordinate distances are aggregated into the same batch, and the orders with insufficient inventory are removed out of the order pool.
The batch aggregation module is further configured to perform the following processes, please refer to fig. 3 at the same time:
step 4-1: path aggregation is carried out on any order pool;
step 4-2: selecting any order in the order pool as a batch first order, and carrying out inventory verification on the order;
step 4-3: judging whether the inventory meets the requirements of all commodities in the order in the inventory verification, if so, entering a step 4-4, and if not, entering a step 4-14; .
Step 4-4: taking the order into a batch as a batch primary order, and deducting corresponding commodity inventory;
and 4-5: calculating the square of the Euclidean distance from all other orders in the order pool to the order;
and 4-6: sorting according to the Euclidean distance from other orders to the first order of the batch from small to large;
and 4-7: taking out the order which is closest to the customer and is not taken into the batch or is not removed, and carrying out inventory check on the order;
and 4-8: judging whether the inventory meets all commodity requirements of the order in inventory verification, if so, switching to a step 4-9, and if not, switching to a step 4-13;
and 4-9: bringing the order into a batch and deducting corresponding commodity inventory;
step 4-10: judging whether the batch is full of orders of the whole batch, if so, switching to the step 4-11, otherwise, switching to the step 4-13;
and 4-11: judging whether all orders in the order pool are aggregated into a batch, if so, switching to the step 4-12, otherwise, returning to the step 4-2;
and 4-12: finishing the batch polymerization;
step 4-13: removing the order from the order pool, reselecting the order, and then switching to the step 4-7;
and 4-14: the order is removed from the order pool and the order is reselected, and then step 4-2 is carried out.
Referring to fig. 5, the system shown in fig. 5 includes a processor and a memory. The memory is configured to store a series of computer-executable instructions and computer-accessible data associated with the series of computer-executable instructions that, when executed by the processor, cause the processor to perform the method as shown in the embodiment of fig. 3.
Furthermore, a non-transitory computer-readable storage medium is disclosed, on which a series of computer-executable instructions are stored, which, when executed by a computing device, cause the computing device to perform the method as shown in the embodiment of fig. 3.
While, for purposes of simplicity of explanation, the methodologies are shown and described as a series of acts, it is to be understood and appreciated that the methodologies are not limited by the order of acts, as some acts may, in accordance with one or more embodiments, occur in different orders and/or concurrently with other acts from that shown and described herein or not shown and described herein, as would be understood by one skilled in the art.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The various illustrative logical blocks, modules, and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.
In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a web site, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk (disk) and disc (disc), as used herein, includes Compact Disc (CD), laser disc, optical disc, Digital Versatile Disc (DVD), floppy disk and blu-ray disc where disks (disks) usually reproduce data magnetically, while discs (discs) reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. An order aggregation method for shortening a warehouse distribution walking path, the method comprising:
the method comprises the following steps: binding the shelf walking index of each storage position;
step two: carrying out initialization processing on the order;
step three: determining a two-dimensional coordinate point of the order in a two-dimensional coordinate system according to the commodity content of the order, wherein the walking index value of the initial goods shelf of each order is an abscissa, and the walking index value of the final goods shelf is an ordinate;
step four: aggregating all orders into a plurality of batches according to the coordinate distances between the two-dimensional coordinate points corresponding to all orders and the stock, wherein the orders with the close coordinate distances are aggregated into the same batch, and the orders with insufficient stock are removed from an order pool;
step five: before generating the batches, sequencing the aggregated batches so that a plurality of adjacent batches cannot be picked from the same channel;
step six: outputting the generated order batch.
2. The order aggregation method for shortening the distribution walking path of the warehouse as claimed in claim 1, wherein the order initialization processing in the second step comprises preliminary screening and sorting of orders, wherein the screening comprises removing orders whose stock cannot meet the demand of goods, the sorting comprises sorting according to order volume, different types of orders are allocated to different order pools, only orders in the same order pool can be aggregated, and orders in different order pools cannot be aggregated.
3. The order aggregation method for shortening a warehouse pick-up travel path as claimed in claim 2, wherein step four further comprises:
step 4-1: path aggregation is carried out on any order pool;
step 4-2: selecting any order in the order pool as a batch first order, and carrying out inventory verification on the order;
step 4-3: judging whether the inventory meets the requirements of all commodities in the order in the inventory verification, if so, entering a step 4-4, and if not, entering a step 4-14; .
Step 4-4: taking the order into a batch as a batch primary order, and deducting corresponding commodity inventory;
and 4-5: calculating the square of the Euclidean distance from all other orders in the order pool to the order;
and 4-6: sorting according to the Euclidean distance from other orders to the first order of the batch from small to large;
and 4-7: taking out the order which is closest to the customer and is not taken into the batch or is not removed, and carrying out inventory check on the order;
and 4-8: judging whether the inventory meets all commodity requirements of the order in inventory verification, if so, switching to a step 4-9, and if not, switching to a step 4-13;
and 4-9: bringing the order into a batch and deducting corresponding commodity inventory;
step 4-10: judging whether the batch is full of orders of the whole batch, if so, switching to the step 4-11, otherwise, switching to the step 4-13;
and 4-11: judging whether all orders in the order pool are aggregated into a batch, if so, switching to the step 4-12, otherwise, returning to the step 4-2;
and 4-12: finishing the batch polymerization;
step 4-13: removing the order from the order pool, reselecting the order, and then switching to the step 4-7;
and 4-14: the order is removed from the order pool and the order is reselected, and then step 4-2 is carried out.
4. An order aggregation system for shortening a warehouse distribution travel path, the system comprising:
the binding module is used for binding the shelf walking index of each storage position;
the order initialization module is used for initializing orders;
the two-dimensional coordinate mapping module is used for determining two-dimensional coordinate points of the orders in a two-dimensional coordinate system according to the commodity contents of the orders, wherein the walking index value of the initial goods shelf of each order is an abscissa, and the walking index value of the final goods shelf is an ordinate;
the batch aggregation module aggregates all orders into a plurality of batches according to the coordinate distances between the two-dimensional coordinate points corresponding to all orders and the inventory, wherein the orders with the close coordinate distances are aggregated into the same batch, and the orders with insufficient inventory are removed from an order pool;
the sorting module sorts the aggregated batches before generating the batches so that a plurality of adjacent batches cannot be picked from the same channel;
and the order batch output module outputs the generated order batch.
5. The order aggregation system for shortening the warehouse distribution travel path of claim 4, wherein the order initialization module is further configured to perform a preliminary screening and sorting of orders, wherein the screening comprises removing orders whose stock cannot meet the demand of the goods, the sorting comprises sorting according to the order volume, different types of orders are allocated to different order pools, only orders in the same order pool can be aggregated, and orders in different order pools cannot be aggregated.
6. The order aggregation system for shortening warehouse distribution travel paths of claim 5, wherein the batch aggregation module is further configured to perform the following processes:
step 4-1: path aggregation is carried out on any order pool;
step 4-2: selecting any order in the order pool as a batch first order, and carrying out inventory verification on the order;
step 4-3: judging whether the inventory meets the requirements of all commodities in the order in the inventory verification, if so, entering a step 4-4, and if not, entering a step 4-14; .
Step 4-4: taking the order into a batch as a batch primary order, and deducting corresponding commodity inventory;
and 4-5: calculating the square of the Euclidean distance from all other orders in the order pool to the order;
and 4-6: sorting according to the Euclidean distance from other orders to the first order of the batch from small to large;
and 4-7: taking out the order which is closest to the customer and is not taken into the batch or is not removed, and carrying out inventory check on the order;
and 4-8: judging whether the inventory meets all commodity requirements of the order in inventory verification, if so, switching to a step 4-9, and if not, switching to a step 4-13;
and 4-9: bringing the order into a batch and deducting corresponding commodity inventory;
step 4-10: judging whether the batch is full of orders of the whole batch, if so, switching to the step 4-11, otherwise, switching to the step 4-13;
and 4-11: judging whether all orders in the order pool are aggregated into a batch, if so, switching to the step 4-12, otherwise, returning to the step 4-2;
and 4-12: finishing the batch polymerization;
step 4-13: removing the order from the order pool, reselecting the order, and then switching to the step 4-7;
and 4-14: the order is removed from the order pool and the order is reselected, and then step 4-2 is carried out.
7. An order aggregation system for shortening a warehouse distribution travel path, the system comprising:
a processor; and
a memory configured to store a series of computer-executable instructions and computer-accessible data associated with the series of computer-executable instructions,
wherein the series of computer executable instructions, when executed by the processor, cause the processor to perform the method of any of claims 1 to 3.
8. A non-transitory computer readable storage medium having stored thereon a series of computer executable instructions that, when executed by a computing device, cause the computing device to perform the method of any of claims 1 to 3.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115130858A (en) * | 2022-06-27 | 2022-09-30 | 上海聚水潭网络科技有限公司 | Order aggregation method and system based on multi-target heuristic method |
| CN115358659A (en) * | 2022-07-21 | 2022-11-18 | 嘉兴聚水潭电子商务有限公司 | Picking batch aggregation method and system based on picking path and electronic equipment |
| CN115439064A (en) * | 2022-09-15 | 2022-12-06 | 江南大学 | Order aggregation-oriented order picking path dynamic optimization method and system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103440566A (en) * | 2013-08-27 | 2013-12-11 | 北京京东尚科信息技术有限公司 | Method and device for generating order picking collection lists and method for optimizing order picking route |
| CN105894358A (en) * | 2016-03-31 | 2016-08-24 | 百度在线网络技术（北京）有限公司 | Commuting order identification method and device |
| CN108280733A (en) * | 2017-01-06 | 2018-07-13 | 阿里巴巴集团控股有限公司 | A kind of order processing system |
| US20180346244A1 (en) * | 2016-01-21 | 2018-12-06 | Cainiao Smart Logistics Holding Limited | Method and device for warehouse storage space planning and electronic device |
| CN109064876A (en) * | 2018-07-25 | 2018-12-21 | 克立司帝控制系统（上海）股份有限公司 | The inflection point edit methods and system of electronic map |
| CN109886478A (en) * | 2019-01-29 | 2019-06-14 | 东南大学 | A kind of slotting optimization method of finished wine automatic stereowarehouse |
| CN110020823A (en) * | 2019-04-09 | 2019-07-16 | 心怡科技股份有限公司 | A kind of storehouse assignment algorithm based on K-Means |
-
2020
- 2020-08-28 CN CN202010887171.6A patent/CN112036635B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103440566A (en) * | 2013-08-27 | 2013-12-11 | 北京京东尚科信息技术有限公司 | Method and device for generating order picking collection lists and method for optimizing order picking route |
| US20180346244A1 (en) * | 2016-01-21 | 2018-12-06 | Cainiao Smart Logistics Holding Limited | Method and device for warehouse storage space planning and electronic device |
| CN105894358A (en) * | 2016-03-31 | 2016-08-24 | 百度在线网络技术（北京）有限公司 | Commuting order identification method and device |
| CN108280733A (en) * | 2017-01-06 | 2018-07-13 | 阿里巴巴集团控股有限公司 | A kind of order processing system |
| CN109064876A (en) * | 2018-07-25 | 2018-12-21 | 克立司帝控制系统（上海）股份有限公司 | The inflection point edit methods and system of electronic map |
| CN109886478A (en) * | 2019-01-29 | 2019-06-14 | 东南大学 | A kind of slotting optimization method of finished wine automatic stereowarehouse |
| CN110020823A (en) * | 2019-04-09 | 2019-07-16 | 心怡科技股份有限公司 | A kind of storehouse assignment algorithm based on K-Means |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115130858A (en) * | 2022-06-27 | 2022-09-30 | 上海聚水潭网络科技有限公司 | Order aggregation method and system based on multi-target heuristic method |
| CN115130858B (en) * | 2022-06-27 | 2024-01-26 | 上海聚水潭网络科技有限公司 | Order aggregation method and system based on multi-objective heuristic |
| CN115358659A (en) * | 2022-07-21 | 2022-11-18 | 嘉兴聚水潭电子商务有限公司 | Picking batch aggregation method and system based on picking path and electronic equipment |
| CN115439064A (en) * | 2022-09-15 | 2022-12-06 | 江南大学 | Order aggregation-oriented order picking path dynamic optimization method and system |
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