WO2019223529A1

WO2019223529A1 - Sorting document generating method and apparatus

Info

Publication number: WO2019223529A1
Application number: PCT/CN2019/085822
Authority: WO
Inventors: 刘国芳
Original assignee: 菜鸟智能物流控股有限公司
Priority date: 2018-05-23
Filing date: 2019-05-07
Publication date: 2019-11-28
Also published as: CN110533350B; CN110533350A

Abstract

The present application provides a sorting document generating method and apparatus: generating a wave picking task for objects to be delivered; classifying the objects to be delivered in the wave picking task according to a preset sorting policy to obtain at least one group; notifying, according to the at least one group, a warehouse system to occupy the stock corresponding to a stock keeping unit (SKU) in the group; and finally generating a sorting document according to storage location occupation information returned by the warehouse system. The purpose of unifying demands of adjacent orders for the same SKU is achieved, so that a warehouse system is able to implement stock occupation in a cluster mode, thus multiple orders can be gathered to be optimized, the probability that the same SKU is occupied at different storage locations for sorting is reduced, the length of a sorting path is reduced, and the sorting efficiency is improved.

Description

Method and device for generating picking list

This application claims priority from a Chinese patent application filed on May 23, 2018 with application number 201810501823.0 and the invention name is "a method and device for generating picking lists", the entire contents of which are incorporated herein by reference.

Technical field

The present application relates to the field of logistics information technology, and in particular, to a method and device for generating a picking list.

Background technique

With the development of e-commerce, more and more users purchase goods online. After the goods are placed into the order system, the order system sends the product order message to the inventory system to take inventory and generate waves for subsequent picking. Process.

At present, the basic unit of a commodity order is a stock keeping unit (SKU, Stock Keeping Unit). After receiving an order, the order system first cuts the order in accordance with the cutting rule to obtain multiple packages, and then calls the inventory system to target The inventory of the SKU in the package is occupied. After the inventory is occupied, the wave task is established and a picking list is generated for subsequent picking, quality inspection, and warehouse delivery.

However, in the current solution, the inventory occupancy of the SKU is performed before the establishment of the wave task, so that the current commodity orders in multiple packages are missing the information about the same SKU from the previous and subsequent commodity orders, so that the inventory occupancy cannot be independently optimized. It will increase the probability that the same SKU will be occupied in different warehouse locations for picking, increase the length of the picking path, and reduce the picking efficiency.

Summary of the Invention

In view of the above problems, an embodiment of the present application provides a picking list generation method to establish a wave task by aggregating objects to be delivered from the warehouse, and to classify the objects to be delivered from the wave task according to a preset picking strategy of the warehouse system Obtaining at least one group for subsequent inventory occupancy, achieving the purpose of unifying the demand for the same SKU between adjacent orders, enabling the warehouse system to occupy inventory in a clustered manner, enabling multiple orders to be aggregated for optimization, The purpose is to occupy the same SKU in the same storage location as much as possible, reducing the probability that the same SKU is occupied in different storage locations for picking, reducing the length of the picking path, and improving the picking efficiency.

Correspondingly, an embodiment of the present application further provides a picking list generating device to ensure the implementation and application of the foregoing method.

In order to solve the above problems, an embodiment of the present application discloses a method for generating a picking list, including:

Generating wave tasks for objects to be shipped out of the warehouse; the objects to be shipped out include inventory units;

Classifying objects to be stored in the wave task according to a preset picking strategy to obtain at least one group;

Notify the warehouse system to occupy the inventory corresponding to the inventory unit in the group according to the group;

Generate picking lists based on the location occupancy information returned by the warehouse system.

Correspondingly, an embodiment of the present application further discloses a picking list generating device, including:

A first wave establishment module, configured to generate a wave task for an object to be taken out of the warehouse; the object to be taken out of the warehouse includes an inventory unit;

A first classification module, configured to classify objects to be stored in the wave task according to a preset picking strategy to obtain at least one group;

A first inventory occupancy module, configured to notify a warehouse system to occupy inventory corresponding to an inventory unit in the group according to the group;

The first picking list generation module is configured to generate a picking list based on the occupancy location information returned by the warehouse system.

On the other hand, the embodiment of the present application discloses another method for generating a picking list, including:

Classify objects to be stored in the wave task to obtain at least one group according to a preset picking strategy;

Occupying the inventory corresponding to the inventory unit in the group according to the group;

Generate picking lists based on occupied locations.

Correspondingly, the embodiment of the present application also discloses another device, including:

A second wave establishment module, configured to generate a wave task for an object to be taken out of the warehouse; the object to be taken out of the warehouse includes an inventory unit;

A second classification module, configured to classify the objects to be warehoused in the wave task to obtain at least one group according to a preset picking strategy;

A second inventory occupancy module, configured to occupy the inventory corresponding to the inventory unit in the group according to the group;

The second picking list generation module is configured to generate a picking list according to the occupied warehouse.

Accordingly, an embodiment of the present application further discloses a device, including:

One or more processors; and one or more machine-readable media having instructions stored thereon, which when executed by the one or more processors, cause the apparatus to perform a pick list generation method.

Correspondingly, the embodiment of the present application also discloses one or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause the apparatus to execute another method for generating a picking list.

The embodiments of the present application include the following advantages:

The embodiments of the present application generate wave tasks for objects to be sent out of the warehouse; classify the objects to be sent out of the wave tasks to obtain at least one group according to a preset picking strategy; and then notify the warehouse system to The inventory corresponding to the inventory unit in the group is occupied; and finally, a picking list is generated based on the location occupation information returned by the warehouse system. In the embodiment of the present application, a wave task is established by summarizing the objects to be delivered from the warehouse, and the objects to be delivered from the wave task are classified according to a preset picking strategy of the warehouse system, and at least one group is obtained to achieve uniformity between adjacent orders. The purpose of the demand for the same SKU enables the warehouse system to occupy inventory in a clustered manner, so that multiple orders can be aggregated for optimization. The purpose is to occupy the same SKU in the same location as much as possible. The probability that the same SKU is occupied for picking in different locations is reduced, the length of the picking path is reduced, and the picking efficiency is improved.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic processing diagram of a picking list generation method according to an embodiment of the present application; FIG.

2 is a flowchart of steps in a method for generating a picking list provided by an embodiment of the present application;

3A is a flowchart of specific steps of a method for generating a picking list provided by an embodiment of the present application;

3B is a schematic diagram of data processing of a first clustering algorithm model provided by an embodiment of the present application;

4 is a flowchart of specific steps of another method for generating a picking list provided by an embodiment of the present application;

5 is a flowchart of steps in another method for generating a picking list provided by an embodiment of the present application;

6 is a structural diagram of a picking list generating device according to an embodiment of the present application;

FIG. 7 is a specific structural diagram of a picking list generating device according to an embodiment of the present application; FIG.

8 is a structural diagram of another picking list generating device according to an embodiment of the present application;

FIG. 9 is a schematic diagram of a hardware structure of a device according to another embodiment of the present application.

Detailed ways

In order to make the foregoing objects, features, and advantages of the present application more comprehensible, the present application is further described in detail below with reference to the accompanying drawings and specific embodiments.

Referring to FIG. 1, a schematic diagram of a picking list generation embodiment of the present application is shown.

It includes a transaction system 10, an order system 20, a warehouse system 30, and a replenishment system 40.

The transaction system 10 includes a client-oriented online shopping application client and a merchant-oriented business application client. The online shopping application client can be used for customers to browse, collect and purchase goods, and the merchant application client can enable merchants to Manage your own stores, such as: placing products, setting product information, and confirming product orders placed by customers.

The order system 20 can receive the order issued by the transaction system 10 and further process the order. Specifically, the order system 20 can establish the wave task for the order or the package according to the order, and the wave order according to the preset picking strategy. The orders or packages in the task are grouped, and the warehouse system 30 is notified according to the group to occupy the inventory corresponding to the inventory unit in the group and generate a picking list.

The warehouse system 30 performs an inventory operation for the SKU after receiving the inventory occupation command issued by the order system 20. If the occupation is successful, the order system 20 is notified to generate a picking list. In addition, if the type of the inventory area occupied by the order is In the replenishment type area, the warehouse system 30 notifies the replenishment system 40 to perform replenishment.

The replenishment system 40 may receive a replenishment order issued by the warehouse system, generate a replenishment order according to the replenishment order, and dispatch a warehouse worker to perform a replenishment operation for the replenishment order.

The specific interaction process is:

A1: The user places an order with the trading system, and the trading system generates a product order.

In the embodiment of the present application, during the online shopping process, the customer can browse on the online shopping application client of the transaction system 10. When the desired product is browsed, the customer will place an order for the product on the online shopping application client , Generate a product order, and send the product order to the merchant application server through the online shopping server.

A2: The trading system sends commodity orders to the order system.

After the merchant confirms the merchandise order through the merchant application client, the merchandise order will be sent by the merchant application server to the order system 20, and the order system 20 will receive the merchandise order. This process is called "order taking", where the merchandise order The content is the SKU of the product and the required quantity for the SKU. SKU means inventory unit, which is defined as the smallest available unit for inventory control. For example, a SKU in textiles usually indicates specifications, colors, and styles.

A3: The order system creates wave tasks for commodity orders.

After the order system 20 receives the order, the order system 20 first establishes a wave task for the order of the product, and aggregates the orders or packages of multiple products into a job unit for sorting operation. The industry usually refers to the batch of this job as the wave. Sub-task, for example: aggregate all orders received from 8 am to 10 am into a wave task, this process is equivalent to aggregating a certain batch of product orders, so that subsequent inventory-taking actions can be based on the wave task's Dimensions.

A4: After the order system has grouped the objects to be shipped out of the wave task according to the preset picking strategy, it will notify the warehouse system to occupy the storage space for the SKU in the classification result.

Further, after the wave task is established, the order system 20 may determine from which storage location in the warehouse system 30 the SKU in the order of the product is selected to obtain the first location information; or call the warehouse system according to the inventory clearance rule 30 performs the SKU occupation in the order for the product, determines which storage location in the warehouse system 30 the SKU is occupied in, and obtains the second location information. The above process is called inventory occupation. For example, 10 SKU1 are required in the order. Then the order system 20 will notify the warehouse system 30 to occupy 10 SKU1 for the order in the storage location corresponding to the SKU1.

Specifically, inventory occupancy includes: when a wave task is established to collect multiple orders or packages of goods, according to the picking strategy specified by the warehouse system 30, the objects to be discharged from the wave task are classified, and multiple groups are obtained. The outbound object can be the package obtained by cutting the box for the order, or it can be the order directly. The picking strategy is a sorting strategy specified according to the picking operation method of the warehouse system 30 or the structure of the package, for example, according to the number of items and the number of items For classification, such as single product, single product, multiple products, multiple products, etc., it can also be classified according to the attributes of the package structure of the product, such as fragile products, and placed face up. Through this picking strategy, at least one grouping can be obtained by classifying objects to be stored in the wave task.

After that, the order system 20 can obtain the first location information and the first picking order information of the storage space occupied by the inventory unit through the first path optimization rule according to the above grouping, and notify the warehouse system 30 of the inventory corresponding to the inventory unit in the group. In addition, according to the above grouping, the order system 20 can also obtain the second location information of the storage location occupied by the inventory unit through the inventory clearance rule, and then obtain the second location of the storage location occupied by the inventory unit through the second path optimization rule. The second picking order information informs the warehouse system 30 to occupy the inventory corresponding to the inventory unit in the group, further optimizing the demand for SKUs between orders, so that SKUs with the same demand can be divided into a category for inventory occupation, which improves the Occupancy accuracy reduces the probability that the same SKU will be occupied in different warehouse locations for picking.

A5: The warehouse system occupies the SKU in the grouping result.

In this step, the action of inventory occupation occurs in the warehouse system 30. The warehouse system 30 can perform inventory occupation corresponding to the inventory unit in the group according to the first location information generated by the order system 20. In addition, the warehouse system 30 can also Clear the inventory rules and obtain the second location information for the inventory occupied by the inventory unit in the group. When the storage system 30 successfully occupies the storage location, it sends the first storage location information or the second storage location information to the order system 20.

A6: The order system generates a picking list based on the location occupancy information returned by the warehouse system.

In this step, the picking list includes: the location information corresponding to the SKUs in the group, and which objects to be sent out of the group form a picking list.

A7: The order system sends the picking list to the warehouse system.

A8: The warehouse system arranges employees for picking according to the picking list.

After the picking list is generated, the order system 20 sends the picking list to the warehouse system 30. The warehouse system 30 assigns employees to pick the information included in the picking list. After the picking of an object to be shipped out, the object can be treated Outbound and subsequent dispatch processes.

In addition, when replenishment is required, step A9 can be performed: when the stock is out of stock, the warehouse system notifies the replenishment system to replenish it.

At present, the inventory occupancy in the prior art occurs before the establishment of wave tasks, and its occupancy actions are random and random. Due to the lack of demand for the same SKU between adjacent orders, there will be a great chance that The same SKU in one wave occupies multiple storage locations, which violates the principle of clearing inventory, which will lead to an increase in the length of the picking path and a reduction in picking efficiency.

Therefore, in the embodiment of the present application, the inventory occupancy action for the SKU occurs after the establishment of the wave task. The embodiment of the present application establishes the wave task by aggregating the objects to be delivered from the warehouse, and The objects to be delivered in the wave task are classified to obtain at least one grouping, which achieves the purpose of unifying the demand for the same SKU between adjacent orders, enabling the warehouse system to occupy inventory in a clustered manner, enabling multiple orders It can be summarized for optimization. The purpose is to occupy the same SKU in the same location as much as possible, reducing the probability that the same SKU is occupied in different locations for picking, reducing the length of the picking path, and improving the efficiency of picking. .

The following describes a picking order generation method through the order system side.

Referring to FIG. 2, a flowchart of steps in an embodiment of a picking list generation method according to the present application is shown, which may specifically include the following steps:

Step 101: Generate a wave task for an object to be delivered from the warehouse; the object to be delivered from the warehouse includes an inventory unit.

In the embodiment of the present application, the order of a product is based on the SKU as the minimum available unit, which contains the SKU of the product and the required quantity for the SKU. For example, a red t-shirt of a certain brand XL code can be called SKU1. 10 pieces are required; a red shirt of L code of a certain brand can be called SKU2, and 5 pieces are required.

Specifically, after the order system receives an order, it will aggregate a certain number of objects to be shipped out of the warehouse as a wave task according to the timing scheduling rule. For example, all orders received from 8 am to 10 am will be aggregated into a wave task. , Or set 3 hours as a time period, aggregate all the objects to be stored in each time period into a wave task.

The process of generating wave tasks is equivalent to aggregating a certain batch of product orders, so that subsequent inventory taking actions can be performed according to the dimensions of wave tasks, avoiding the lack of a current order and its neighboring orders for the same SKU. Information, so that inventory occupancy can be optimized for subsequent inventory occupancy actions in the dimension of wave tasks.

Step 102: According to a preset picking strategy, classify objects to be stored in the wave task to obtain at least one group.

In the embodiment of the present application, the picking strategy is a sorting strategy stipulated according to the picking operation method of the warehouse system or the structure of the package. For example, the sorting is based on the number of items and the number of items, such as single product, single product, multiple products, multiple products. Etc., single product refers to the same SUK, multiple product refers to multiple different SKUs, single product refers to the demand quantity is 1 unit, and multiple product refers to the demand quantity is multiple. In addition, you can also classify products according to their package structure attributes, such as fragile products and placing them face up.

For example, suppose that according to the number of products and the number of items, the five objects to be shipped out of a wave task are classified.

Objects to be shipped out 1 include SKU1, 1 item; SKU2, 1 item.

Objects to be shipped 2 include SKU1 and 1 item.

Objects to be taken out 3 include SKU1 and 4 pieces.

Objects to be shipped out 4 include SKU1, 3 pieces; SKU2, 4 pieces; SKU3, 1 piece.

Objects to be shipped out 5 include SKU2, 1 item.

Then, the classification result is that the object 1 to be shipped out is multiple items and multiple pieces, the object to be shipped out is 2 items and single items, the object to be shipped out is 3 items and multiple items, and the object to be shipped out 4 is multiple items and multiple pieces. There are 5 single items and single items to be shipped out of the warehouse. Therefore, the five objects to be discharged are divided into three groups. Subsequent inventory occupancy can be performed independently according to these three groups.

It should be noted that the objects of the package structure can also be classified according to the package structure attributes of the object to be shipped, such as fragile products, and placed face up. The classification strategy is based on the appearance structure and packaging structure of the objects to be shipped. The classification results can meet the needs of the picking operation method of the warehouse system. For example, the warehouse system has a corresponding picking method for fragile products and another corresponding picking method for products that need to be placed face up. The above classification method can be adopted. Aggregate objects to be shipped from the same demand into the same category.

Through the preset picking strategy, at least one group can be classified into the out-of-warehouse objects in the wave task, which further optimizes the demand for SKUs between orders, so that SKUs with the same demand can be divided into a category for inventory occupation. , Improve the occupation accuracy, reduce the probability of the same SKU being occupied in different warehouse locations for picking.

Step 103: According to the group, the warehouse system is notified to occupy the inventory corresponding to the inventory unit in the group.

In the embodiment of the present application, the order system decomposes the inventory information into the form of a three-level ledger to occupy the different level ledger by the SKU.

The primary account is the general ledger of the warehouse, which is the inventory information of the entire warehouse of the SKU, which mainly includes the following information: product ID, positive and defective status, total physical inventory, total saleable inventory, total occupied inventory, etc.

The secondary account is a storage area type account. In addition to the contents of the primary account, the storage area type and SKU occupation data during the operation are added. The types of storage area are: stocking area, picking area, temporary storage. Area, defective area, differential inventory area, etc.

The tertiary account is the warehouse location account. The core expression is the number of SKUs in a warehouse area.

In the embodiment of the present application, the occupancy action of the primary account and the secondary account occurs before the establishment of the wave task, and the purpose is to determine whether there is a shortage of inventory and the occupancy data between the same order system, transaction system, and warehouse system. This step is mainly based on the tertiary account. There are two main ways to use the inventory for the group generated in step 103:

Method 1: The order system obtains the inventory location distribution information of the location of the SKU in the group by querying the three-level account information of the warehouse system, and then determines the location information of the location occupied by the SKU in the group through the path optimization rule. , And which group of objects to be warehoused in the group form a picking list, and then send the location information of the location occupied by the SKU to the warehouse system for the warehouse system to take the action.

Method 2: For each group, the order system uses the inventory clearing rule and the first-in-first-out rule to notify the warehouse system to occupy the inventory corresponding to the SKU in the group. After the occupation is successful, it is determined through the route optimization rules based on the occupied location information. Which of the objects to be put out of the group constitutes a picking list. The inventory clearing rule is that for the storage location corresponding to a SKU, the storage location is filled before the next storage location corresponding to the SKU is occupied. Higher. The first-in-first-out rule means that in the inventory management, the chronological order of the SKUs into the warehouse is sorted, and the operation is based on the principle of the SKUs that are put in the warehouse first.

Based on the two above-mentioned occupancy methods, the first method has higher operation accuracy than the second method, which can effectively reduce the picking path, and the second method has a higher occupation efficiency, which can meet the inventory surge in orders such as “Double 11”. Take up the need for efficiency.

Step 104: Generate a picking list based on the occupancy location information returned by the warehouse system.

In the embodiment of the present application, after the warehouse system completes the occupation of the at least one group of storage locations, it sends the successful occupancy information to the order system. The order system uses the location information of the storage locations occupied by the SKUs in the group, and Several objects to be sent out of the warehouse constitute the information of a picking list, and a picking list is generated. The content of the picking list is to inform the warehouse staff which SKUs are included in an object to be sent out of the warehouse, and which storage location these SKUs go to for picking. Warehouse staff can perform picking operations quickly and accurately according to the picking list.

In summary, a picking list generation method provided in the embodiments of the present application is to generate wave tasks for objects to be sent out of the warehouse; classify the objects to be sent out of the wave tasks according to a preset picking strategy to obtain At least one group; then, according to the at least one group, the warehouse system is notified to occupy the inventory corresponding to the inventory unit in the group; and finally, a picking list is generated according to the location occupation information returned by the warehouse system. In the embodiment of the present application, a wave task is established by summarizing the objects to be delivered from the warehouse, and the objects to be delivered from the wave task are classified according to a preset picking strategy of the warehouse system, and at least one group is obtained to achieve uniformity between adjacent orders The purpose of the demand for the same SKU enables the warehouse system to occupy inventory in a clustered manner, so that multiple orders can be aggregated for optimization. The purpose is to occupy the same SKU in the same location as much as possible. The probability that the same SKU is occupied for picking in different locations is reduced, the length of the picking path is reduced, and the picking efficiency is improved.

The following describes the interaction process of the picking list generation method through the order system and the logistics system.

Referring to FIG. 3A, a flow chart of specific steps of a method for generating a picking list of the present application is shown, which may specifically include the following steps:

Step 201: The order system receives an order.

In the process of online shopping, the transaction system includes customer-oriented online shopping applications and merchant-oriented merchant platform applications. Customers will browse on the online shopping application. When they browse the favorite product, they will place an order for the product and generate Product order. The content of a product order is the SKU of the product and the required quantity for the SKU. In the embodiment of the present application, an order for a commodity is sent to an order system by a merchant platform application of a trading system, and this process is called “order receiving”.

In step 202, the order system sends the order to the warehouse system, and notifies the warehouse system to perform warehouse general ledger occupation for the order.

In the embodiment of the present application, after the order system receives the order, the order and its details are stored, and then a MetaQ message including the order and its details is sent to the warehouse system for the warehouse system to store the order and its details. This process is a warehouse Orders from the system.

In step 203, the warehouse system performs warehouse general ledger occupancy for the inventory unit in the order according to the order.

In this step, the warehouse system uses the warehouse general ledger for the inventory unit in the order according to the obtained order, that is, the primary account is occupied. The purpose of occupying the primary account is to determine whether the total inventory of a SKU meets the SKU in the order. If the demand is met, the occupation is successful. If it is not met, the trading system will be reminded that the stock is out of stock.

Step 204: If the warehouse general ledger fails to be used, the warehouse system notifies the order system and the transaction system that the order is out of stock.

In the embodiment of the present application, if the general ledger of the warehouse fails, it means that the inventory for the SKU in the warehouse is insufficient. At this time, the order system and the trading system need to be informed that the SKU in the order is out of stock and needs to be replenished. After the goods are successfully delivered, you can continue to occupy the warehouse ledger of the SKU.

Step 205: If the warehouse general ledger is successfully occupied, the warehouse system broadcasts the successful occupation information to the transaction system and the order system.

In the embodiment of the present application, if the warehouse general ledger is successfully occupied, the warehouse system broadcasts the successful occupation information to the transaction system and the order system to achieve the purpose of unifying data between the three systems, enabling subsequent processes.

In step 206, the order system notifies the warehouse system to occupy the warehouse area type for the order.

In the embodiment of the present application, after the warehouse system occupies the primary account, the type of storage area can be used, that is, the secondary account. The purpose is to determine whether the SKU has goods in the warehouse's picking area (subsequent sorting action) Is the picking in the picking area of the SKU in the warehouse). It should be noted that the occupancy of the secondary account needs to be processed according to the warehouse order rules of the warehouse, and the occupancy of the secondary account and the occupancy of the primary account in step 203 must be uniform according to the scheduling rules and at a preset time. Scheduling, for example, processing the primary and secondary account occupancy actions of 10 objects out of the warehouse every 2 hours to improve occupancy efficiency.

Step 207: The warehouse system occupies the warehouse area type for the order.

In step 208, if the type of storage area occupied by the order is a warehouse picking area, step 211 is performed.

In the embodiment of the present application, the types of storage areas included in the secondary account are: stocking area, picking area, temporary storage area, scrap area, differential inventory area, etc., while the picking operation can only pick SKUs in the picking area. Therefore, when the type of storage area occupied by the order is a warehouse picking area, it means that the inventory of the SKU in the picking area can meet the demand of the order. At this time, step 211 is performed. According to the preset cutting rule, the order system The inventory unit performs the box cutting operation to obtain the action of the package object. After the package is obtained, the wave task for the package can be established.

Step 209: If the type of the warehouse area occupied by the order is a replenishment type area, the warehouse system notifies the replenishment system to replenish.

In this step, if the type of storage area occupied by the order is a replenishment type area, it means that the inventory of the SKU in the picking area cannot meet the demand of the order. At this time, the replenishment system needs to be notified to replenish the SKU warehouse area, where The replenishment type area can be a stocking area, a temporary storage area, a defective area, a differential inventory area, and so on.

Step 210: The replenishment system replenishes the warehouse picking area.

In the embodiment of the present application, the replenishment system for replenishing the warehouse picking area may specifically include: the replenishment system dispatches warehouse workers to generate replenishment orders for operations according to certain rules and priorities, and after the replenishment is completed, the warehouse The system will cycle the secondary account occupation for this SKU until the occupation is successful.

Step 211: According to a preset box-cutting rule, the order system performs a box-cut operation on the inventory unit in the order to obtain a parcel object.

In the embodiment of the present application, the box cutting is a pre-processing action for orders. The purpose is to aggregate the SKUs in the order according to the dimensions of appearance and packaging attributes to obtain packages. At that time, the packages will flow into the package pool to be summarized. The processing is directed at the package.

For example, the order structure is as follows: (unit: mm, structure: length, width, height)

Product 1 size: 160 mm, 60 mm, 270 mm; number: 3 pieces.

Commodity 2 size: 110 mm, 30 mm, 150 mm; number: 2 pieces.

Product 3 size: 90mm, 50mm, 180mm; number: 2

The size of the cartons in the warehouse system has the following specifications: (unit: mm, structure: length, width, height)

Carton No. 1: 120mm, 111mm, 261mm.

Carton No. 2: 245mm, 220mm, 370mm.

Carton No. 3: 295 mm, 240 mm, 390 mm.

Then, according to the quantity and structural specifications of the goods included in the order, the box is determined to choose the carton No. 2 to pack all the goods in the order to get the package, so that the subsequent process can be carried out in accordance with the dimensions of the package, which facilitates subsequent picking and delivery Inventory and distribution processes.

In step 212, the order system generates a wave task for the parcel object.

Optionally, a wave task for the order may also be generated. In this case, no box cutting action is required, which simplifies the process of generating picking lists.

In the embodiment of the present application, the object on which the wave task is established may be an order or a package, which is not limited in the embodiment of the present application. Preferably, a wave task for the package object may be established to enable subsequent processes. It is carried out in accordance with the dimensions of the package, which facilitates the subsequent picking, storage and distribution processes.

Optionally, step 212 further includes sub-step 2121.

Sub-step 2121: Adjust a wave number task threshold of the wave task according to a preset load balancing policy, and the wave number task threshold is a number of wave task executions within a preset time.

In the embodiment of the present application, the load balancing strategy means that the number of executions of wave tasks within a preset time must meet the requirement of uniform and no fluctuations, because the scheduling machine works similarly to a computer's process management and is divided into multiple scheduling processes. For the execution of wave tasks, for example, the maximum number of wave times for a task to be run by a scheduling process is set to 5. Therefore, an optimal wave task threshold can be obtained based on experiments. By setting the wave task The number of thresholds can avoid the occurrence of jamming of the task waves of the scheduling machine and improve the execution efficiency of the task waves.

Step 213: According to a preset picking strategy, the order system sorts the objects to be stored in the wave task to obtain at least one group.

For step 213, reference may be made to the description of step 102 above, and details are not described herein again.

Step 214: The order system acquires the location inventory distribution information of the location that stores the inventory unit in the group.

In this step, the order system can obtain the location inventory distribution information of the SKU in the warehouse system, that is, the three-level ledger. The inventory location distribution information is the library updated after the previous wave task processing. Bit inventory distribution information can be used as the basis for subsequent inventory occupancy processes in this wave task to determine which location can be occupied by the corresponding SKU and which location cannot be occupied by the corresponding SKU.

Step 215: According to the inventory location distribution information, the ordering system uses a first path optimization rule to determine the grouped first picking order information and the first picking location information corresponding to the first picking order information; wherein, the The first location information is the location information of the location occupied by the inventory unit in the first picking order information; the sum of the picking paths of the first picking order information is the shortest.

In the embodiment of the present application, according to the storage location inventory distribution information, a path optimization may be performed on the occupied storage location of the SKU through a first path optimization rule to determine the first storage location information and the first picking order information, and the first storage location. The information indicates the information about the location occupied by the SKU in the package included in a group. The location information includes the physical location information of the location, and the first pick list information includes those packages in the group to form a pick list. The first path optimization rule further optimizes the demand for SKUs between orders, so that SKUs with the same demand can be divided into a category for inventory occupation, which improves the occupation accuracy and reduces the same SKU being occupied in different warehouses. The probability of picking at the location.

Optionally, the first path optimization rule includes a first clustering algorithm model and a first genetic algorithm model. Step 215 may further include sub-step 2151 and sub-step 2152.

Sub-step 2151: According to the inventory location distribution information, the order system uses the first clustering algorithm model to re-cluster the objects to be stored in each group.

In this step, there are multiple types of clustering algorithm models that can be used. This application uses the Kmeans clustering model as an example for illustration. Specifically, the Kmeans algorithm is the most classic partition-based clustering method, and it is one of the ten classic data mining algorithms. The basic idea of the Kmeans algorithm is: clustering with k points in space as the center, classify the objects closest to them, and iteratively update the values of each cluster center one by one until the best clustering result is obtained. .

For example: In a package group, the SKUs included in the package are:

Parcel 1: sku1, sku2, sku3;

Parcel 2: sku2, sku3, sku4, sku8;

Parcel 3: sku5, sku6, sku8;

Parcel 4: sku7, sku8, sku10;

Parcel 5: sku1, sku9.

The stock situation is:

sku1: zone1, zone2, zone3;

sku2: zone2, zone3;

sku3: zone4;

sku4: zone1, zone5;

sku5: zone5, zone6;

sku6: zone1;

sku7: zone5, zone6, zone7;

sku8: zone6, zone7;

sku9: zone7;

sku10: zone2.

It can be seen that the wrapped vector is expressed as: (zone1, zone2, zone3, zone4, zone5, zone6, zone7)

Among them, according to the location inventory distribution information, if the corresponding SKU included in the package can satisfy its occupation, the dimension vector value is 1, otherwise it is 0.

It can be seen that the wrapping vector is:

Parcel 1: [1,1,1,1,0,0,0]

Parcel 2: [1,1,1,1,1,1,1]

Parcel 3: [1,0,0,0,1,1,1]

Parcel 4: [0,1,0,0,1,1,1]

Parcel 5: [1,1,1,0,0,0,1]

Assume that the number of Kmeans classification is two, that is, two picking lists are generated, and the convergence goal is: the sum of the picking paths of SKUs in the picking list is the shortest.

At this time, two centroid points of the cluster are randomly selected: Parcel 1 and Parcel 2. According to the jaccrod similarity, the objects in the same cluster have a high similarity; and the objects in different clusters have a small similarity. Steps 1 to 4 shown in FIG. 3B are performed until the convergence result is obtained. It should be noted that, for example, the jaccrod distance between the parcel 1 and the parcel 2 is 4/7 = 0.57.

It can be known from FIG. 3B that, in the end, the parcel 1 and the parcel 5 are of one type, and constitute a picking list, and the parcel 2, parcel 3, and parcel 4 are of another type, forming another picking list. And the corresponding SKU is selected in the storage location of the vector value of 1 in the parcel vector.

It should be noted that the first clustering algorithm model may be calculated using a Kmeans algorithm model, or may be calculated using a clustering model with other similar functions, which is not limited in this application.

In sub-step 2152, the clustering result is used as the initial first picking order information, and the order system uses the first genetic algorithm model to optimize the initial first picking order information to obtain the first picking order information with the shortest sum of the picking paths.

In this step, the re-clustering result obtained in the sub-step 2151 is used as the initial first picking list information, and the initial first picking list information can be further optimized through the first genetic algorithm model to obtain the final optimal solution.

Specifically, further optimization of the initial first picking list information through the first genetic algorithm model includes the following steps:

In step S1, an initial solution is constructed. Specifically, the initial encoding of the solution of the problem, that is, the re-clustering result obtained in substep 21121 is used as the initial solution, and the vector form of 0-1 is encoded according to the rules. Generally, two initial solutions are required as the parent and the parent, and calculated The fitness of the parent and the mother. The fitness here is the sum of the selection paths in the selection list.

In step S2, a new solution is generated. Specifically, the parent and the mother are crossed and mutated to generate a new solution. The crossover strategy generally uses truncation and swap, and the mutation strategy generally uses a fixed mutation probability or a decay mutation probability.

Step S3, fine-tuning to a feasible solution. The new solution generated in step S2 may not satisfy the constraint conditions. Therefore, the new solution is adjusted in the domain so that it satisfies the constraints and at the same time adaptability of the new solution.

In step S4, the process from step 2 to step 3 is repeated. Specifically, the parent and the parent with the highest fitness in the current sequence are selected, and the cross mutation process is repeated until the sequence length is satisfied.

In step S5, the solution with the highest fitness is output, and the solution is the first picking list information with the shortest sum of the picking paths.

Step 216: The order system sends the first storage location information to the warehouse system for the warehouse system to occupy the corresponding storage location according to the first storage location information.

In this step, the first location information is used to determine which location of the SKU packaged in the group to occupy, and the warehouse system performs the location occupancy action of the SKU for the first location information.

Further, according to the grouping, the warehouse system may be notified to occupy a storage location in the warehouse picking area.

In the embodiment of the present application, the types of storage areas included in the secondary account are: stocking area, picking area, temporary storage area, scrap area, differential inventory area, etc., while the picking operation can only pick SKUs in the picking area. Therefore, when the type of warehouse area occupied by the order is a warehouse picking area, it means that the SKU inventory in the picking area can meet the demand of the order.

Step 217: The warehouse system occupies the corresponding storage location according to the first storage location information.

Step 218: When receiving the first location occupancy message of the warehouse system, the order system generates a first picking list according to the first picking order information and the first location information corresponding to the first picking order information.

In the embodiment of the present application, after the warehouse system completes the occupation of the corresponding location according to the first location information, the successful occupation information is sent to the order system, and the order system according to the first location of the location occupied by the SKU in the group Information, and which several packages in the group constitute the first picking order information of a picking list to generate a first picking list. The first picking list contains information that tells warehouse employees which SKUs are included in a package, and these SKUs. Which warehouse location to go for picking, the warehouse staff can quickly and accurately perform the picking action according to the picking list.

In summary, a picking list generation method provided in FIG. 3A in the embodiment of the present application. The ordering system generates wave tasks for objects to be shipped out of the warehouse, and then performs processing on the objects to be shipped out of the wave tasks according to a preset picking strategy. Classify to get at least one group, and then the order system obtains the location inventory distribution information of the SKU locations in the group by querying the tertiary account information of the warehouse system, and then determines the SKUs in the group by the path optimization rules. Location information, and which objects in the group are to be sent out to form a picking list, and then the location information of the SKU occupied location is sent to the warehouse system for the warehouse system to take the action. When the occupation is completed, the order The system generates a first picking list.

An embodiment of the present application provides a picking list generation method by generating wave tasks for objects to be delivered from a warehouse; classifying the objects to be delivered from a wave task according to a preset picking strategy to obtain at least one group; According to at least one group, the warehouse system is notified to occupy the inventory corresponding to the inventory unit in the group; and finally, a picking list is generated according to the location occupation information returned by the warehouse system. In the embodiment of the present application, a wave task is established by summarizing the objects to be delivered from the warehouse, and the objects to be delivered from the wave task are classified according to a preset picking strategy of the warehouse system, and at least one group is obtained to achieve uniformity between adjacent orders The purpose of the demand for the same SKU enables the warehouse system to occupy inventory in a clustered manner, so that multiple orders can be aggregated for optimization. The purpose is to occupy the same SKU in the same location as much as possible. The probability that the same SKU is occupied for picking in different locations is reduced, the length of the picking path is reduced, and the picking efficiency is improved.

The following describes the interaction process of another picking order generation method through the order system and logistics system.

Referring to FIG. 4, a flowchart of specific steps of another method for generating a picking list of the present application is shown, which may specifically include the following steps:

Step 301: The order system receives an order.

Optionally, step 301 may refer to the description of step 201 above, and details are not described herein again.

In step 302, the order system sends the order to the warehouse system, and notifies the warehouse system to perform the warehouse general ledger occupation for the order.

Optionally, for step 302, reference may be made to the description of step 202 above, and details are not described herein again.

In step 303, the warehouse system performs warehouse general ledger occupation for the inventory unit in the order according to the order.

Optionally, for step 303, reference may be made to the description of step 203, and details are not described herein again.

In step 304, if the warehouse general ledger fails to be used, the warehouse system notifies the order system and the transaction system that the order is out of stock.

Optionally, step 304 may refer to the description of step 204 described above, and details are not described herein again.

Step 305: If the warehouse general ledger is successfully occupied, the warehouse system broadcasts the successful occupation information to the transaction system and the order system.

Optionally, for step 305, reference may be made to the description of step 205, and details are not described herein again.

In step 306, the order system notifies the warehouse system to occupy the warehouse area type for the order.

Optionally, for step 306, reference may be made to the description of step 206, and details are not described herein again.

Step 307: The warehouse system occupies the warehouse area type for the order.

In step 308, if the type of storage area occupied by the order is a warehouse picking area, step 311 is performed.

Optionally, for step 308, reference may be made to the description of step 208, and details are not described herein again.

Step 309: If the type of the warehouse area occupied by the order is a replenishment type area, the warehouse system notifies the replenishment system to replenish.

Optionally, for step 309, reference may be made to the description of step 209, and details are not described herein again.

Step 310: The replenishment system replenishes the warehouse picking area.

Optionally, for step 310, reference may be made to the description of step 210 above, and details are not described herein again.

Step 311: According to a preset box-cutting rule, the order system performs a box-cut operation on the inventory unit in the order to obtain a parcel object.

Optionally, for step 311, reference may be made to the description of step 211, and details are not described herein again.

In step 312, the order system generates a wave task for the parcel object.

Optionally, step 312 may refer to the description of step 212, and details are not described herein again.

Optionally, step 312 further includes sub-step 3121.

Sub-step 3121, adjusting a wave number task threshold of the wave task according to a preset load balancing policy, and the wave number task threshold is a number of wave task executions within a preset time.

Optionally, step 3121 may refer to the description of step 2121 described above, and details are not described herein again.

Step 313: According to a preset picking strategy, the order system sorts the objects to be stored in the wave task to obtain at least one group.

Optionally, for step 313, reference may be made to the description of step 213, and details are not described herein again.

Step 314: The order system sends the group to the warehouse system for the warehouse system to occupy the inventory corresponding to the inventory unit in the group according to the inventory clearance rule.

In the embodiment of the present application, for each group, the order system uses the inventory clearing rule and the first-in-first-out rule to notify the warehouse system to occupy the inventory corresponding to the SKU in the group. After the occupation is successful, according to the occupied location information, the path is passed. The optimization rule determines which packages in the group form a picking list. The inventory clearing rule is that for the storage location corresponding to a SKU, the storage location is filled before the next storage location corresponding to the SKU is occupied. Higher efficiency. The first-in-first-out rule means that in the inventory management, the chronological order of the SKUs into the warehouse is sorted, and the operation is based on the principle of the SKUs that are put in the warehouse first.

Step 315: The warehouse system occupies the inventory corresponding to the inventory unit in the group according to the inventory clearing rule.

In step 316, the order system receives a second storage location occupancy message returned by the warehouse system.

In this step, according to the inventory clearing rule in step 314, the warehouse system occupies the inventory corresponding to the inventory unit in the group. After completing the occupation, the warehouse system sends the successful occupation information to the order system. The second location information of the location occupied by the SKU is obtained through the second path optimization rule to obtain the grouped second picking order information.

Step 317: According to the second storage location occupancy message, the order system uses a second path optimization rule to determine the grouped second picking order information; the sum of the picking paths of the second picking order information is the shortest.

Optionally, the second path optimization rule includes a second clustering algorithm model and a second genetic algorithm model. The sub-step 317 may further include a sub-step 3171 and a sub-step 3172.

Sub-step 3171, according to the second storage location occupation message, the order system uses the second clustering algorithm model to re-cluster the objects to be stored in each group.

Different from the example of step 2151 in a picking order generation method provided in FIG. 3A, the SKU inventory and parcel vector expressions in the package in sub-step 3171 are based on the SKU through the inventory clearance rule or the FIFO rule in step 314. The second clustering algorithm model can be calculated by using the Kmeans algorithm model, or by using other clustering models with similar functions. The application does not limit this.

In sub-step 3172, the clustering result is used as the initial second picking order information. The order system uses a second genetic algorithm model to optimize the initial second picking order information to obtain the second picking order information with the shortest sum of the picking paths.

This step may refer to the description of sub-step 2152 in a picking list generation method provided in FIG. 3A, which is not described in the embodiment of the present application.

It should be noted that, since the second location occupancy message has been obtained according to the inventory clearing rule in step 314, the result obtained in substep 3172 is the second picking order information with the shortest sum of the picking paths.

Step 318: The order system generates a second picking order according to the second picking order information.

In the embodiment of the present application, the content of the second picking list is to inform the warehouse employees which SKUs are included in the package, and which storage locations are occupied by these SKUs through the inventory clearing rule. The warehouse employee can use the picking list, Quick and precise picking.

In summary, another picking order generation method provided in FIG. 4 in the embodiment of the present application. The ordering system generates wave tasks for objects to be shipped from the warehouse, and then according to a preset picking strategy, processes the objects to be shipped from the waves. Classify to get at least one group, and then for each group, the order system uses the inventory clearing rule and the FIFO rule to notify the warehouse system to occupy the inventory corresponding to the SKU in the group. After the occupation is successful, according to the occupied location information, The path optimization rules are used to determine which objects in the group to be taken out of the warehouse constitute a picking list. The inventory clearing rule is that for the storage location corresponding to a SKU, the storage location is filled before the next SKU corresponding to the SKU. The occupancy of the storage location is more efficient. The first-in-first-out rule means that in the inventory management, the chronological order of the SKUs into the warehouse is sorted, and the operation is based on the principle of the SKUs that are put in the warehouse first.

Based on the two storage space occupation methods provided in FIGS. 3A and 4 respectively, the operation accuracy of the method of FIG. 3A is higher than that of FIG. 4, which can effectively reduce the picking path, and the occupation efficiency of the method of FIG. 4 is higher. It can meet the demand for efficiency of inventory occupancy during the surge in orders such as “Double 11”. Specifically, during the surge in orders, the method in Figure 4 can use the inventory clearance rules to occupy the inventory first, and then simply The route optimization is performed to obtain the picking order information and generate the picking order. Although the accuracy of the occupied space is not as shown in Figure 3A, its sorting efficiency when facing large-volume orders is higher than the method shown in Figure 3A. In practical applications, different occupancy methods can be selected according to requirements, which is not limited in this application.

Referring to FIG. 5, there is shown a flowchart of steps of another method for generating a picking list of the present application, which may specifically include the following steps:

Step 401: Generate a wave task for an object to be delivered from the warehouse; the object to be delivered from the warehouse includes an inventory unit.

For step 401, reference may be made to the description of step 101 above, and details are not described herein again.

Step 402: Classify the objects to be stored in the wave task to obtain at least one group according to a preset picking strategy.

For step 402, reference may be made to the description of step 102 above, and details are not described herein again.

Step 403: Occupy the inventory corresponding to the inventory unit in the group according to the group.

For step 403, when the warehouse system and the order system can be aggregated into a total system, step 403 can use the total system to occupy the inventory corresponding to the inventory unit in the group according to the group. In addition, the warehouse system and the order system can also cooperate to complete the execution of step 403. For details, reference may be made to the description of step 403, and details are not described herein again.

Step 404: Generate a picking list based on the occupied locations.

For step 404, when the warehouse system and the order system can be aggregated into one overall system, step 404 can generate a picking list by the overall system according to the occupied storage locations. In addition, the execution of step 404 may also be completed by the warehouse system and the order system. For details, reference may be made to the description of step 404, and details are not described herein again.

In summary, a picking list generation method provided in the embodiments of the present application is to generate wave tasks for objects to be sent out of the warehouse; classify the objects to be sent out of the wave tasks according to a preset picking strategy to obtain At least one group; then, according to the at least one group, the warehouse system is notified to occupy the inventory corresponding to the inventory unit in the group; and finally, a picking list is generated according to the location occupation information returned by the warehouse system. In the embodiment of the present application, a wave task is established by summarizing the objects to be delivered from the warehouse, and the objects to be delivered from the wave task are classified according to a preset picking strategy of the warehouse system, and at least one group is obtained to achieve uniformity between adjacent orders. The purpose of the demand for the same SKU enables the warehouse system to occupy inventory in a clustered manner, so that multiple orders can be aggregated for optimization. The purpose is to occupy the same SKU in the same location as much as possible. The probability that the same SKU is occupied for picking in different locations is reduced, the length of the picking path is reduced, and the picking efficiency is improved.

It should be noted that, for the method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the embodiments of the present application are not limited by the described action sequence because According to the embodiment of the present application, some steps may be performed in other orders or simultaneously. Secondly, a person skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present application.

Referring to FIG. 6, a structural diagram of a picking list generating device in a specific example of the present application is shown, which may specifically include the following modules:

The first wave establishment module 501 is configured to generate a wave task for an object to be delivered from the warehouse; the object to be delivered from the warehouse includes an inventory unit.

A first classification module 502 is configured to classify objects to be stored in the wave task according to a preset picking strategy to obtain at least one group.

The first inventory occupancy module 503 is configured to notify the warehouse system to occupy the inventory corresponding to the inventory unit in the group according to the group.

The first picking list generation module 504 is configured to generate a picking list according to the occupancy location information returned by the warehouse system.

Referring to FIG. 7, a specific structural diagram of a picking list generating device in a specific example of the present application is shown, which may specifically include the following modules:

The order receiving module 601 is configured to receive an order.

The general ledger occupation module 602 is configured to notify the warehouse system to perform warehouse general ledger occupation for the order.

Optionally, the general ledger occupation module 602 further includes:

The first general ledger occupation submodule is configured to notify the trading system that the order is out of stock if the warehouse general ledger occupation fails.

The second general ledger occupation submodule is configured to broadcast successful occupation information if the warehouse general ledger occupation is successful.

The warehouse area occupancy module 603 is configured to notify the warehouse system to occupy a warehouse area type for the order.

The picking area occupancy module 604 is configured to execute a step of generating a wave task for an object to be delivered if the type of the warehouse area occupied by the order is a warehouse picking area.

The replenishment module 605 is configured to notify the replenishment system to replenish if the type of the warehouse area occupied by the order is a replenishment type area.

The box cutting module 606 is configured to perform a box cutting operation on the inventory unit in the order according to a preset box cutting rule to obtain a parcel object.

The first wave establishment module 607 is configured to generate a wave task for an object to be delivered from the warehouse; the object to be delivered from the warehouse includes an inventory unit.

Optionally, the first wave establishment module 607 includes:

The order wave generation submodule is used to generate a wave task for the order.

A wrapped wave generation sub-module is used to generate a wave task for the wrapped object.

A load balancing module 608 is configured to adjust a wave number task threshold of the wave task according to a preset load balancing policy, and the wave number task threshold is a number of wave task executions within a preset time.

A first classification module 609 is configured to classify objects to be stored in the wave task according to a preset picking strategy to obtain at least one group.

The first inventory occupancy module 610 is configured to notify the warehouse system to occupy the inventory corresponding to the inventory unit in the group according to the group.

Optionally, the first inventory occupation module 610 includes:

An acquisition submodule, configured to acquire the location inventory distribution information of the location that stores the inventory unit in the group;

A first optimization submodule, configured to determine the grouped first picking order information and the first picking order information corresponding to the first picking order information according to the inventory location distribution information and using a first path optimization rule; The first location information is the location information of the location occupied by the inventory unit in the first picking order information; the sum of the picking paths of the first picking order information is the shortest;

A second occupancy submodule is configured to send the group to the warehouse system for the warehouse system to occupy the inventory corresponding to the inventory unit in the group according to the inventory clearance rule.

The storage location occupancy submodule is configured to notify a warehouse system to occupy a storage location in the warehouse picking area according to the grouping.

Optionally, the first optimization sub-module includes:

A first clustering unit, configured to re-cluster the objects to be discharged from each group by using the first clustering algorithm model according to the inventory location distribution information;

A first genetic optimization unit, configured to use the clustering result as initial first picking order information, optimize the initial first picking order information using a first genetic algorithm model, and obtain first picking order information having a shortest sum of the picking paths .

A first occupancy submodule is configured to send the first storage location information to the warehouse system for the warehouse system to occupy a corresponding storage location according to the first storage location information.

The first picking list generation module 611 is configured to generate a picking list according to the storage space occupancy information returned by the warehouse system.

Optionally, the first picking list generation module 611 includes:

A first generating submodule, configured to generate a first picking according to the first picking order information and the first picking order information corresponding to the first picking order information when receiving the first picking position occupancy message of the warehouse system; single.

A receiving submodule, configured to receive a second storage location occupancy message returned by the warehouse system;

A second optimization sub-module, configured to determine a second picking order information of the group by using a second path optimization rule according to the second location occupation message; the sum of the picking paths of the second picking order information is the shortest;

Optionally, the second optimization sub-module includes:

A second clustering unit, configured to re-cluster the to-be-deposited objects in each group by using the second clustering algorithm model according to the second location occupancy message;

A second genetic optimization unit, configured to use the clustering result as the initial second picking order information, optimize the initial second picking order information using a second genetic algorithm model, and obtain the second picking order information with the shortest sum of the picking paths .

A second generating sub-module is configured to generate a second picking list according to the second picking list information.

Referring to FIG. 8, a structural diagram of another picking list generating device in a specific example of the present application is shown, which may specifically include the following modules:

The second wave establishment module 701 is configured to generate a wave task for an object to be delivered from the warehouse; the object to be delivered from the warehouse includes an inventory unit;

A second classification module 702, configured to classify objects to be stored in the wave task to obtain at least one group according to a preset picking strategy;

A second inventory occupancy module 703, configured to occupy the inventory corresponding to the inventory unit in the group according to the group;

The second picking list generation module 704 is configured to generate a picking list according to the occupied storage space.

In summary, a picking list generating device provided in the embodiments of the present application generates wave tasks for objects to be sent out of the warehouse; according to a preset picking strategy, classifies the objects to be sent out of the wave tasks to obtain At least one group; then, according to the at least one group, the warehouse system is notified to occupy the inventory corresponding to the inventory unit in the group; and finally, a picking list is generated according to the location occupation information returned by the warehouse system. In the embodiment of the present application, a wave task is established by summarizing the objects to be delivered from the warehouse, and the objects to be delivered from the wave task are classified according to a preset picking strategy of the warehouse system, and at least one group is obtained to achieve uniformity between adjacent orders. The purpose of the demand for the same SKU enables the warehouse system to occupy inventory in a clustered manner, so that multiple orders can be aggregated for optimization. The purpose is to occupy the same SKU in the same location as much as possible. The probability that the same SKU is occupied for picking in different locations is reduced, the length of the picking path is reduced, and the picking efficiency is improved.

As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple. For the relevant part, refer to the description of the method embodiment.

FIG. 9 is a schematic structural diagram of a server according to an embodiment of the present application. Referring to FIG. 9, the server 800 may be used to implement the method for determining a wave task provided in the foregoing embodiment. The server 800 may have relatively large differences due to different configurations or performance, and may include one or more central processing units (CPUs) 822 (for example, one or more processors) and memory 832, one or one The above storage medium 830 (for example, one or one storage device) storing the application program 842 or the data 844. The memory 832 and the storage medium 830 may be temporarily stored or persistently stored. The program stored in the storage medium 830 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations on the server. Furthermore, the central processing unit 822 may be configured to communicate with the storage medium 830 and execute a series of instruction operations in the storage medium 830 on the server 800.

The server 800 may also include one or more power sources 826, one or more wired or wireless network interfaces 850, one or more input-output interfaces 858, one or more keyboards 856, and / or, one or more operating systems 841. , Such as Windows ServerTM, Mac OSXTM, UnixTM, LinuxTM, FreeBSDTM and so on. The central processing unit 822 may execute the following operations on the server 800:

A picking list is generated according to the storage location occupancy information returned by the warehouse system.

Optionally, the one or more modules may have the following functions:

Obtaining the inventory location distribution information of the inventory locations storing the inventory quantity units in the group;

Determining the grouped first picking order information and the first picking order information corresponding to the first picking order information according to the inventory location distribution information by using a first path optimization rule; wherein the first inventory position information Is the location information of the location occupied by the inventory unit in the first picking order information; the sum of the picking paths of the first picking order information is the shortest;

Sending the first storage location information to the warehouse system for the warehouse system to occupy a corresponding storage location according to the first storage location information.

Optionally, the first path optimization rule includes a first clustering algorithm model and a first genetic algorithm model. According to the inventory location distribution information, the first clustering algorithm model is used for each group in each group. Re-cluster the outbound objects;

The clustering result is used as the initial first picking list information, and the first genetic algorithm model is used to optimize the initial first picking list information to obtain the first picking list information with the shortest sum of the picking paths.

Optionally, when receiving the first location occupancy message of the warehouse system, a first picking list is generated according to the first picking order information and the first location information corresponding to the first picking order information.

Optionally, the group is sent to the warehouse system for the warehouse system to occupy the inventory corresponding to the inventory unit in the group according to the inventory clearance rule.

Optionally, receiving a second location occupancy message returned by the warehouse system;

Determining the second picking order information of the group according to the second location occupation message using a second path optimization rule; the sum of the picking paths of the second picking order information is the shortest;

Generate a second picking list according to the second picking list information.

Optionally, the second path optimization rule includes a second clustering algorithm model and a second genetic algorithm model;

Use the second clustering algorithm model to re-cluster the objects to be stored in each group according to the second location occupancy message;

The clustering result is used as the initial second picking list information, and the second genetic algorithm model is used to optimize the initial second picking list information to obtain the second picking list information with the shortest sum of the picking paths.

Optionally, receive the order.

Optionally, a wave task for the order is generated.

Optionally, according to a preset load balancing strategy, a threshold of the number of wave tasks of the wave task is adjusted, and the threshold of the number of wave tasks is the number of executions of the wave task within a preset time.

Optionally, according to a preset box cutting rule, a box cutting operation is performed on the inventory unit in the order to obtain a parcel object.

Optionally, a wave task for the wrapped object is generated.

Optionally, the warehouse system is notified to occupy a warehouse area type for the order;

If the type of the warehouse area occupied by the order is a warehouse picking area, performing a step of generating a wave task for the object to be delivered from the warehouse;

If the type of the warehouse area occupied by the order is a replenishment type area, the replenishment system is notified to replenish.

Optionally, according to the grouping, a warehouse system is notified to occupy a storage location in the warehouse picking area.

Optionally, the warehouse system is notified to perform a warehouse general ledger occupation for the inventory unit in the order.

Optionally, if the warehouse general ledger fails to be used, the trading system is notified that the order is out of stock.

Optionally, if the warehouse general ledger is successfully occupied, the successful occupation information is broadcast.

This application provides a device having one or more machine-readable media having instructions stored thereon, which when executed by the one or more processors, causes the device to execute a picking list generation method.

This application also provides one or more machine-readable media having instructions stored thereon that, when executed by one or more processors, cause the device to execute a picking list generation method.

The present application provides a device having one or more machine-readable media having instructions stored thereon, which when executed by the one or more processors, causes the device to execute another method for generating a pick list.

The application also provides one or more machine-readable media having instructions stored thereon that, when executed by one or more processors, cause the apparatus to execute another method for generating a pick list.

Each embodiment in this specification is described in a progressive manner. Each embodiment focuses on the differences from other embodiments, and the same or similar parts between the various embodiments may refer to each other.

Those skilled in the art should understand that the embodiments of the embodiments of the present application may be provided as a method, an apparatus, or a computer program product. Therefore, the embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the embodiments of the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

The embodiments of the present application are described with reference to flowcharts and / or block diagrams of the method, the terminal device (system), and the computer program product according to the embodiments of the present application. It should be understood that each process and / or block in the flowcharts and / or block diagrams, and combinations of processes and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing terminal device Means are generated for implementing the functions specified in one or more flowcharts and / or one or more blocks of the block diagrams.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including the instruction device, The instruction means implements the functions specified in one or more flowcharts and / or one or more blocks of the block diagram.

These computer program instructions can also be loaded on a computer or other programmable data processing terminal device, so that a series of operation steps can be performed on the computer or other programmable terminal device to produce a computer-implemented process, so that the computer or other programmable terminal device can The instructions executed on the steps provide steps for implementing the functions specified in one or more of the flowcharts and / or one or more of the block diagrams.

Although the preferred embodiments of the embodiments of the present application have been described, those skilled in the art can make other changes and modifications to these embodiments once they know the basic inventive concepts.

Finally, it should be noted that in this article, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply these entities. There is any such actual relationship or order between OR operations. Moreover, the terms "including", "comprising", or any other variation thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or terminal device that includes a series of elements includes not only those elements but also those that are not explicitly listed Other elements, or elements inherent to such a process, method, article, or terminal. Without more restrictions, the elements defined by the sentence "including a ..." do not exclude the existence of other identical elements in the process, method, article, or terminal device including the elements.

The method and device for generating a picking list provided in the present application have been described in detail above. Specific examples are used in this document to explain the principle and implementation of the present application. The description of the above embodiments is only used to help understand the present application. Method and its core ideas; at the same time, for those of ordinary skill in the art, according to the ideas of this application, there will be changes in the specific implementation and application scope. In summary, the contents of this description should not be understood as Restrictions on this application.

Claims

A picking list generation method is characterized in that it includes:

Generating wave tasks for objects to be shipped out of the warehouse; the objects to be shipped out include inventory units;

Classifying objects to be stored in the wave task according to a preset picking strategy to obtain at least one group;

Notify the warehouse system to occupy the inventory corresponding to the inventory unit in the group according to the group;

A picking list is generated according to the storage location occupancy information returned by the warehouse system.
The method according to claim 1, wherein the step of notifying a warehouse system to occupy inventory corresponding to an inventory unit in the group according to the grouping comprises:

Obtaining the inventory location distribution information of the inventory locations storing the inventory quantity units in the group;

Determining the grouped first picking order information and the first picking order information corresponding to the first picking order information according to the inventory location distribution information by using a first path optimization rule; wherein the first inventory position information Is the location information of the location occupied by the inventory unit in the first picking order information; the sum of the picking paths of the first picking order information is the shortest;

Sending the first storage location information to the warehouse system for the warehouse system to occupy a corresponding storage location according to the first storage location information.
The method according to claim 2, wherein the first path optimization rule comprises a first clustering algorithm model and a first genetic algorithm model; and the first path optimization is used according to the inventory location distribution information. The step of determining the grouped first picking order information and the first location information corresponding to the first picking order information includes:

Using the first clustering algorithm model to re-cluster the objects to be discharged from each group according to the inventory location distribution information;

The clustering result is used as the initial first picking list information, and the first genetic algorithm model is used to optimize the initial first picking list information to obtain the first picking list information with the shortest sum of the picking paths.
The method according to claim 3, wherein the step of generating a picking list based on the location occupancy information returned by the warehouse system comprises:

When the first storage location occupancy message of the warehouse system is received, a first picking list is generated according to the first picking order information and first storage location information corresponding to the first picking order information.
The method according to claim 1, wherein the step of notifying a warehouse system to occupy inventory corresponding to an inventory unit in the group according to the grouping comprises:

And sending the group to the warehouse system for the warehouse system to occupy the inventory corresponding to the inventory unit in the group in accordance with the inventory clearance rule.
The method according to claim 5, wherein the step of generating a picking list based on the storage location occupancy information returned by the warehouse system comprises:

Receiving a second location occupancy message returned by the warehouse system;

Determining the second picking order information of the group according to the second location occupation message using a second path optimization rule; the sum of the picking paths of the second picking order information is the shortest;

Generate a second picking list according to the second picking list information.
The method according to claim 6, wherein the second path optimization rule comprises a second clustering algorithm model and a second genetic algorithm model; and according to the second location occupation message, a second path optimization rule is used The step of determining the second picking order information of the group includes:

Use the second clustering algorithm model to re-cluster the objects to be stored in each group according to the second location occupancy message;

The clustering result is used as the initial second picking list information, and the second genetic algorithm model is used to optimize the initial second picking list information to obtain the second picking list information with the shortest sum of the picking paths.
The method according to claim 1, further comprising:

Receive the order.
The method according to claim 8, wherein the step of generating a wave task for an object to be decommissioned comprises:

Generate wave tasks for the order.
The method according to claim 9, further comprising:

According to a preset load balancing strategy, a threshold of the number of wave tasks of the wave task is adjusted, and the threshold of the number of wave tasks is the number of executions of the wave task within a preset time.
The method according to claim 8, further comprising:

Carry out a box cutting operation on the inventory unit in the order according to a preset box cutting rule to obtain a parcel object.
The method according to claim 11, wherein the step of generating a wave task for an object to be sent out comprises:

Generate a wave task for the wrapped object.
The method according to claim 9, before the step of generating wave tasks for the order, further comprising:

Notifying the warehouse system to occupy a warehouse area type for the order;

If the type of the warehouse area occupied by the order is a warehouse picking area, performing a step of generating a wave task for the object to be delivered from the warehouse;

If the type of the warehouse area occupied by the order is a replenishment type area, the replenishment system is notified to replenish.
The method according to claim 13, wherein the step of notifying the warehouse system to occupy the inventory corresponding to the inventory unit in the group according to the grouping comprises:

According to the grouping, the warehouse system is notified to occupy a storage location in the warehouse picking area.
The method according to claim 8, further comprising:

Notifying the warehouse system to perform warehouse general ledger occupancy for the inventory unit in the order.
The method according to claim 15, further comprising:

If the warehouse general ledger fails, the trading system is notified that the order is out of stock.
The method according to claim 15, further comprising:

If the warehouse ledger is successfully occupied, the successful occupation information is broadcast.
A picking list generation method is characterized in that it includes:

Generating wave tasks for objects to be shipped out of the warehouse; the objects to be shipped out include inventory units;

Classify objects to be stored in the wave task to obtain at least one group according to a preset picking strategy;

Occupying the inventory corresponding to the inventory unit in the group according to the group;

Generate picking lists based on occupied locations.
A picking list generating device, comprising:

A first wave establishment module, configured to generate a wave task for an object to be taken out of the warehouse; the object to be taken out of the warehouse includes an inventory unit;

A first classification module, configured to classify objects to be stored in the wave task according to a preset picking strategy to obtain at least one group;

A first inventory occupancy module, configured to notify a warehouse system to occupy inventory corresponding to an inventory unit in the group according to the group;

The first picking list generation module is configured to generate a picking list based on the occupancy location information returned by the warehouse system.
The device according to claim 19, wherein the first inventory occupancy module comprises:

An acquisition submodule, configured to acquire the location inventory distribution information of the location that stores the inventory unit in the group;

A first optimization submodule, configured to determine the grouped first picking order information and the first picking order information corresponding to the first picking order information according to the inventory location distribution information and using a first path optimization rule; The first location information is the location information of the location occupied by the inventory unit in the first picking order information; the sum of the picking paths of the first picking order information is the shortest;

A first occupancy submodule is configured to send the first storage location information to the warehouse system for the warehouse system to occupy a corresponding storage location according to the first storage location information.
The device according to claim 20, wherein the first path optimization rule comprises a first clustering algorithm model and a first genetic algorithm model; and the first optimization sub-module comprises:

A first clustering unit, configured to re-cluster the objects to be discharged from each group by using the first clustering algorithm model according to the inventory location distribution information;

A first genetic optimization unit, configured to use the clustering result as initial first picking order information, optimize the initial first picking order information using a first genetic algorithm model, and obtain first picking order information having a shortest sum of the picking paths .
The device according to claim 21, wherein the first picking list generation module comprises:

A first generating submodule, configured to generate a first picking according to the first picking order information and the first picking order information corresponding to the first picking order information when receiving the first picking position occupancy message of the warehouse system; single.
The device according to claim 19, wherein the first inventory occupancy module comprises:

A second occupancy submodule is configured to send the group to the warehouse system for the warehouse system to occupy the inventory corresponding to the inventory unit in the group according to the inventory clearance rule.
The apparatus according to claim 23, wherein the first picking list generation module comprises:

A receiving submodule, configured to receive a second storage location occupancy message returned by the warehouse system;

A second optimization sub-module, configured to determine a second picking order information of the group by using a second path optimization rule according to the second location occupation message; the sum of the picking paths of the second picking order information is the shortest;

A second generating sub-module is configured to generate a second picking list according to the second picking list information.
The apparatus according to claim 24, wherein the second optimization sub-module comprises:

A second clustering unit, configured to re-cluster the to-be-deposited objects in each group by using the second clustering algorithm model according to the second location occupancy message;

A second genetic optimization unit, configured to use the clustering result as the initial second picking order information, optimize the initial second picking order information using a second genetic algorithm model, and obtain the second picking order information with the shortest sum of the picking paths .
The apparatus according to claim 19, further comprising:

An order receiving module is used to receive an order.
The apparatus according to claim 26, wherein the first wave establishment module comprises:

The order wave generation submodule is used to generate a wave task for the order.
The apparatus according to claim 27, further comprising:

A load balancing module is configured to adjust a wave number task threshold of the wave task according to a preset load balancing policy, and the wave number task threshold is a number of wave task executions within a preset time.
The apparatus according to claim 26, further comprising:

The box cutting module is configured to perform a box cutting operation on the inventory unit in the order according to a preset box cutting rule to obtain a parcel object.
The apparatus according to claim 29, wherein the first wave establishment module comprises:

A wrapped wave generation sub-module is used to generate a wave task for the wrapped object.
The apparatus according to claim 27, further comprising:

A warehouse area occupancy module, configured to notify the warehouse system to occupy a warehouse area type for the order;

The picking area occupancy module is configured to execute the step of generating wave tasks for objects to be delivered from the warehouse if the type of storage area occupied by the order is a warehouse picking area;

The replenishment module is configured to notify the replenishment system to replenish if the type of the warehouse area occupied by the order is a replenishment type area.
The apparatus according to claim 31, wherein the first inventory occupancy module comprises:

The storage location occupancy submodule is configured to notify a warehouse system to occupy a storage location in the warehouse picking area according to the grouping.
The apparatus according to claim 26, further comprising:

The general ledger occupation module is used to notify the warehouse system to perform warehouse general ledger occupation for the order.
The apparatus according to claim 33, further comprising:

The first general ledger occupation submodule is configured to notify the trading system that the order is out of stock if the warehouse general ledger occupation fails.
The apparatus according to claim 33, further comprising:

The second general ledger occupation submodule is configured to broadcast successful occupation information if the warehouse general ledger occupation is successful.
A picking list generating device, comprising:

A second wave establishment module, configured to generate a wave task for an object to be taken out of the warehouse; the object to be taken out of the warehouse includes an inventory unit;

A second classification module, configured to classify the objects to be warehoused in the wave task to obtain at least one group according to a preset picking strategy;

A second inventory occupancy module, configured to occupy the inventory corresponding to the inventory unit in the group according to the group;

The second picking list generation module is configured to generate a picking list according to the occupied warehouse.
A picking list generating device, comprising:

One or more processors; and

One or more machine-readable media having instructions stored thereon, when executed by the one or more processors, cause the apparatus to perform the method of any one of claims 1-17.
One or more machine-readable media having stored thereon instructions that, when executed by one or more processors, cause a device to perform the method of any one of claims 1-17.
A picking list generating device, comprising:

One or more processors; and

One or more machine-readable media having instructions stored thereon, when executed by the one or more processors, cause the apparatus to perform the method of claim 18.
One or more machine-readable media having stored thereon instructions that, when executed by one or more processors, cause a device to perform the method of claim 18.