CN110533350B

CN110533350B - Method and device for generating picking order

Info

Publication number: CN110533350B
Application number: CN201810501823.0A
Authority: CN
Inventors: 刘国芳
Original assignee: Cainiao Smart Logistics Holding Ltd
Current assignee: Cainiao Smart Logistics Holding Ltd
Priority date: 2018-05-23
Filing date: 2018-05-23
Publication date: 2023-11-07
Anticipated expiration: 2038-05-23
Also published as: WO2019223529A1; CN110533350A

Abstract

The application provides a method and a device for generating a picking order, which are used for generating a wave order task aiming at an object to be delivered; classifying objects to be delivered in the wave order task according to a preset picking strategy to obtain at least one group; then, according to at least one group, informing a warehouse system to occupy the inventory corresponding to the inventory units in the group; and finally, generating a picking order according to the bin occupation information returned by the warehouse system. The aim of unifying the requirements of adjacent orders on the same SKU is achieved, the warehouse system can carry out inventory occupation according to a clustering mode, a plurality of orders can be summarized to be optimized, the probability that the same SKU is occupied in different warehouse positions to pick is reduced, the length of a picking path is further reduced, and the picking efficiency is improved.

Description

Method and device for generating picking order

Technical Field

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

Background

With the development of electronic commerce, more and more users purchase commodities on the internet, and after the commodities are ordered to an order system, the order system sends commodity order information to an inventory system to occupy inventory and generate wave numbers so as to carry out a picking process subsequently.

At present, the basic unit of commodity orders is stock quantity units (SKUs, stock Keeping Unit), after order taking, an order system firstly cuts the order according to a box cutting rule to obtain a plurality of packages, then invokes the stock system to carry out stock occupation aiming at SKUs in the packages, after the stock occupation is completed, the establishment of wave order tasks is carried out, and a picking order is generated for carrying out practical operation operations such as follow-up picking, quality inspection, warehouse-out and the like.

However, in the current scheme, because the inventory occupation of SKUs is performed before the wave order task is established, the current commodity orders in the packages lack the requirement information of the front commodity order and the back commodity order for the same SKU, so that the inventory occupation cannot be independently optimized, the probability that the same SKU is occupied in different warehouse positions to pick is increased, the length of a picking path is increased, and the picking efficiency is reduced.

Disclosure of Invention

In view of the above problems, an embodiment of the present application provides a method for generating a picking order, so as to obtain at least one group for performing subsequent inventory occupation by summarizing objects to be taken out of a warehouse to build a wave order task and classifying the objects to be taken out of the wave order task according to a preset picking policy of a warehouse system, thereby achieving the purpose of unifying requirements of adjacent orders for the same SKU, so that the warehouse system can perform inventory occupation in a clustered manner, and a plurality of orders can be summarized for optimization.

Correspondingly, the embodiment of the application also provides a device for generating the picking list, which is used for ensuring the realization and the application of the method.

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

generating a wave task aiming at an object to be taken out of the warehouse; the object to be delivered comprises a stock quantity unit;

classifying objects to be delivered in the wave order task according to a preset picking strategy to obtain at least one group;

according to the grouping, informing a warehouse system to occupy the inventory corresponding to the inventory units in the grouping;

and generating a picking order according to the warehouse position occupation information returned by the warehouse system.

Correspondingly, the embodiment of the application also discloses a device for generating the picking list, which comprises the following steps:

the first wave number establishing module is used for generating a wave number task aiming at an object to be delivered; the object to be delivered comprises a stock quantity unit;

the first classification module is used for classifying objects to be delivered in the wave order task according to a preset picking strategy to obtain at least one group;

the first inventory occupation module is used for informing a warehouse system to occupy the inventory corresponding to the inventory units in the group according to the group;

The first picking order generation module is used for generating a picking order according to the warehouse position occupation information returned by the warehouse system.

In another aspect, an embodiment of the present application discloses another method for generating a pick order, including:

occupying an inventory corresponding to the inventory units in the group according to the group;

and generating a picking order according to the occupied library positions.

Correspondingly, the embodiment of the application also discloses another device, which is characterized by comprising:

the second wave number establishing module is used for generating a wave number task aiming at the object to be delivered; the object to be delivered comprises a stock quantity unit;

the second classification module is used for classifying objects to be delivered in the wave order task according to a preset picking strategy to obtain at least one group;

the second inventory occupation module is used for occupying the inventory corresponding to the inventory units in the group according to the group;

and the second picking order generation module is used for generating the picking order according to the occupied storage position.

Correspondingly, the embodiment of the application also discloses a device, which is characterized by comprising:

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 order generation method.

Accordingly, embodiments of the present application also disclose one or more machine-readable media having instructions stored thereon that, when executed by one or more processors, cause an apparatus to perform another pick order generation method.

one or more processors; and

The embodiment of the application has the following advantages:

the embodiment of the application generates the wave task aiming at the object to be delivered; classifying objects to be delivered in the wave order task according to a preset picking strategy to obtain at least one group; then, according to at least one group, informing a warehouse system to occupy the inventory corresponding to the inventory units in the group; and finally, generating a picking order according to the bin occupation information returned by the warehouse system. According to the embodiment of the application, the wave order tasks are built by summarizing the objects to be delivered, and the objects to be delivered in the wave order tasks are classified according to the preset picking strategy of the warehouse system, so that at least one group is obtained, the aim of unifying the demands of adjacent orders for the same SKU is fulfilled, the warehouse system can carry out inventory occupation according to a clustering mode, a plurality of orders can be summarized for optimization, the aim is to occupy the same SKU in the same warehouse position as much as possible, the probability of occupying the same SKU in different warehouse positions for picking is reduced, the picking path length is reduced, and the picking efficiency is improved.

Drawings

FIG. 1 is a schematic diagram illustrating a method for generating a pick order according to an embodiment of the present application;

FIG. 2 is a flow chart of steps of a method for generating a pick order according to an embodiment of the present application;

FIG. 3A is a flowchart illustrating steps of a method for generating a pick order according to an embodiment of the present application;

FIG. 3B is a schematic diagram illustrating data processing of a first clustering algorithm model according to an embodiment of the present application;

FIG. 4 is a flowchart illustrating steps of another method for generating a pick order according to an embodiment of the present application;

FIG. 5 is a flow chart of steps of another method for generating a pick order provided by an embodiment of the present application;

FIG. 6 is a block diagram of a pick order generation device according to an embodiment of the present application;

FIG. 7 is a specific block diagram of a pick order generation device according to an embodiment of the present application;

FIG. 8 is a block diagram of another pick order generation device provided in accordance with an embodiment of the present application;

fig. 9 is a schematic hardware structure of an apparatus according to another embodiment of the present application.

Detailed Description

In order that the above-recited objects, features and advantages of the present application will become more readily apparent, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description.

Referring to FIG. 1, a schematic diagram of one pick order generation embodiment of the present application is shown.

Which includes a transaction system 10, an order system 20, a warehouse system 30, and a restocking system 40.

The transaction system 10 includes a client-oriented online shopping application client and a merchant application client facing a merchant, wherein the online shopping application client can provide clients with operations such as browsing, collecting and purchasing commodities, and the merchant application client can enable the merchant to manage stores under the self-flags, such as: putting the commodity on shelf, setting commodity information, confirming commodity orders issued by clients, and the like.

The order system 20 may receive orders placed by the trading system 10 and further process the orders, specifically: the order system 20 may perform establishment of a wave order task for an order or a package according to an order, group the order or the package in the wave order task according to a preset picking policy, notify the warehouse system 30 to occupy an inventory corresponding to a stock quantity unit in the group according to the group, and generate a picking order.

The warehouse system 30 performs the inventory occupying operation for SKUs after receiving the inventory occupying command issued by the order system 20, and if the inventory occupying is successful, notifies the order system 20 to generate a pick order, and if the type of the warehouse area occupied by the order is a replenishment type area, the warehouse system 30 notifies the replenishment system 40 to perform replenishment.

The restocking system 40 may receive restocking commands issued by the warehouse system, generate restocking orders according to the restocking commands, and send restocking operations for the restocking orders.

The specific interaction process is as follows:

a1: the user places an order to a trading system, which generates a commodity order.

In the embodiment of the application, in the online shopping process, a customer can browse on an online shopping application client of the transaction system 10, when browsing the commodity of the cardiometer, the customer can make a ordering action for the commodity on the online shopping application client to generate a commodity order, and the commodity order is sent to a merchant application server through an online shopping server.

A2: the trading system sends the order for the merchandise to the order system.

After the merchant confirms the order for the commodity through the merchant application client, the order for the commodity is sent by the merchant application server to the order system 20, and the order system 20 receives the order for the commodity, a process called "order taking", wherein the commodity order contains the SKU of the commodity and the required quantity for the SKU. SKU means stock quantity unit, defined as the smallest available unit to hold stock control, e.g., one SKU in a textile typically represents a specification, color, style.

A3: the order system establishes a wave order task for the commodity order.

After the order system 20 takes an order, the order system 20 first establishes a wave order task for the order of the commodity, and gathers the orders or packages of the multiple commodities into a unit of operation for sorting, and the batch of the operation is generally referred to as the wave order task in the industry, for example: all orders received from 8 to 10 in the morning are collected into a wave order task, and the process is equivalent to aggregation of a certain batch of commodity orders, so that the follow-up inventory occupying action can be performed according to the dimension of the wave order task.

A4: after grouping objects to be delivered in the wave order task according to a preset picking strategy, the order system informs the warehouse system of occupying the warehouse positions aiming at the SKU in the classification result.

Further, after the wave order task is established, the order system 20 may determine from which bin in the warehouse system 30 the SKU in the order of the commodity is picked, to obtain the first bin information; or according to the inventory cleaning rule, the warehouse system 30 is called to perform SKU occupation in the order for the commodity, which bin in the warehouse system 30 is occupied by the SKU, and the second bin information is obtained, where the process is called inventory occupation, for example, 10 SKUs 1 are required in the order, and the order system 20 notifies the warehouse system 30 that 10 SKUs 1 are occupied for the order at the bin corresponding to SKU1.

Specifically, inventory occupancy includes: after the order or package of the multiple commodities is summarized by the wave order task, sorting objects to be delivered in the wave order task according to a sorting strategy specified by the warehouse system 30 to obtain multiple groups, wherein the objects to be delivered can be packages obtained by cutting boxes for the order, or can be directly orders, and the sorting strategy is a sorting strategy specified according to a sorting operation mode of the warehouse system 30 or a structure of the packages, for example: the goods are classified according to the number and the number of the goods, such as single goods, multiple goods and multiple goods, and the like, and the goods can be classified according to the wrapping structure attributes of the goods, such as fragile goods, upward placement on the front surface and the like. By means of the sorting strategy, objects to be delivered in the wave order tasks can be classified to obtain at least one group.

Then, the order system 20 may obtain, according to the above grouping, the first bin information and the first order picking information of the bin occupied by the stock quantity unit through the first path optimization rule, notify the warehouse system 30 to occupy the bins corresponding to the stock quantity unit in the grouping, in addition, the order system 20 may also obtain, according to the above grouping, the second bin information of the bin occupied by the stock quantity unit through the stock clearing rule, and notify the warehouse system 30 to occupy the bins corresponding to the stock quantity unit in the grouping through the second order picking information of the bin occupied by the second path optimization rule, so that the requirements of SKUs with the same requirements are further optimized, and SKUs with the same requirements can be classified into one category to occupy the bins, thereby improving the accuracy of the occupation, and reducing the probability that the same SKU is occupied in different warehouse bins to pick.

A5: the warehouse system performs warehouse bit occupation for SKUs in the grouping result.

In this step, the action of inventory occupation occurs in the warehouse system 30, and the warehouse system 30 may perform inventory occupation corresponding to the inventory units in the group according to the first inventory information generated by the order system 20, and in addition, the warehouse system 30 may further obtain the second inventory information for inventory occupation corresponding to the inventory units in the group according to the inventory clearing rule. After the warehouse system 30 successfully occupies the warehouse site, the first warehouse site information or the second warehouse site information is sent to the order system 20.

A6: and the order system generates a picking order according to the bin occupation information returned by the warehouse system.

In this step, the pick order includes: the occupied bin position information corresponding to the SKU in the group and which objects to be taken out form a picking list in the group.

A7: the order system sends the pick order to the warehouse system.

A8: the warehouse system arranges staff to pick according to the pick order.

After the picking order is generated, the order system 20 issues the picking order to the warehouse system 30, and the warehouse system 30 dispatches staff to pick the information included in the picking order, so that when the picking of the object to be picked is completed, the object to be picked can be picked and the subsequent dispatching process can be performed.

In addition, when restocking is required, step A9 may be performed: when out of stock, the warehouse system notifies the restocking system to restock.

At present, the inventory occupation in the prior art occurs before the establishment of the wave order task, the occupation action is disordered and random, and because the requirement for the same SKU is lacking between adjacent orders, a great probability is generated that the same SKU in one wave order occupies a plurality of warehouse positions, the inventory clearance principle is violated, the picking path length is increased, and the picking efficiency is reduced.

Therefore, in the embodiment of the application, the inventory occupation action aiming at the SKU occurs after the establishment of the wave order task, and the embodiment of the application obtains at least one group by summarizing the objects to be delivered in the wave order task and classifying the objects to be delivered in the wave order task according to the preset picking strategy of the warehouse system, thereby achieving the purpose of unifying the requirements of the same SKU among adjacent orders, ensuring that the warehouse system can carry out inventory occupation in a clustering way, ensuring that a plurality of orders can be summarized for optimization, and aiming at occupying the same SKU in the same bin as much as possible, reducing the probability of picking by occupying the same SKU in different bins, reducing the picking path length and improving the picking efficiency.

A method of generating a pick order is described below by the order system side.

Referring to fig. 2, a flowchart illustrating steps of an embodiment of a method for generating a pick order according to the present application may specifically include the following steps:

step 101, generating a wave task aiming at an object to be delivered; the object to be ex-warehouse includes a stock quantity unit.

In the embodiment of the application, the order of the commodity takes the SKU as the minimum available unit, and the content contained in the order is the SKU of the commodity and the required quantity aiming at the SKU, such as: a red body shirt of certain brand XL code, which may be called SKU1, requires 10 pieces; a brand L code red body shirt, which may be referred to as SKU2, requires 5 pieces.

Specifically, after the order system receives an order, a certain number of objects to be delivered are aggregated as a wave task according to a regular scheduling rule, for example: all orders received from 8 to 10 in the morning are collected to be a wave task, or 3 hours are set to be a time period, and all objects to be ex-warehouse in each time period are aggregated to be a wave task.

The process of generating the wave order task is equivalent to aggregation of a certain batch of commodity orders, so that the follow-up inventory occupying action can be performed according to the dimension of the wave order task, the problem that one current order lacks information of the same SKU requirement of an order adjacent to the current order is avoided, the inventory occupying action can be optimized according to the dimension of the wave order task, and the follow-up inventory occupying action can be performed.

Step 102, classifying objects to be delivered in the wave order task according to a preset picking strategy to obtain at least one group.

In the embodiment of the application, the picking strategy is a classification strategy defined according to the picking operation mode of the warehouse system or the structure of the package, for example: the goods are classified according to the number and the number of the goods, such as single goods, multiple goods and the like, wherein the single goods refer to the same SUK, the multiple goods refer to multiple different SKUs, the single piece refers to the 1-piece required number, and the multiple pieces refer to the multiple required numbers. In addition, the commodities can be classified according to the wrapping structure attributes of the commodities, such as fragile products, upward-facing attributes and the like.

For example, it is assumed that 5 objects to be taken out of a warehouse, which are included in one wave task, are classified according to the number of products and the number of pieces of products.

The object to be delivered 1 comprises SKU1 and 1 piece; SKU2,1 piece.

The object to be delivered 2 comprises SKU1,1 piece.

The object to be delivered 3 comprises SKU1,4 pieces.

The object to be delivered 4 comprises SKU1 and 3 pieces; SKU2,4 pieces; SKU3,1 piece.

The object to be delivered 5 includes SKU2, 1.

And the classification result is that the object 1 to be delivered is multiple pieces, the object 2 to be delivered is a single piece, the object 3 to be delivered is multiple pieces, the object 4 to be delivered is multiple pieces, and the object 5 to be delivered is a single piece. Thus, five objects to be taken out are divided into 3 groups. Subsequent inventory occupancy may occur independently in these three groupings.

It should be noted that, the sorting policy may be classified according to the package structure attribute of the object to be sorted, such as the fragile product, the front side up, etc., so that the sorting result may meet the requirement of the sorting operation mode of the warehouse system, for example, the warehouse system has a corresponding sorting mode for the fragile product, and another corresponding sorting mode for the commodity to be sorted front side up, and the objects to be sorted with the same requirement may be aggregated into the same sorting through the above sorting mode.

Through presetting a picking strategy, objects to be taken out of the warehouse in wave order tasks can be classified to obtain at least one group, requirements on SKUs among orders are further optimized, the SKUs with the same requirements can be classified into one class to be occupied by the inventory, the occupied accuracy is improved, and the probability that the same SKU is occupied in different warehouse positions to be picked is reduced.

And step 103, notifying a warehouse system to occupy the inventory corresponding to the stock quantity unit in the group according to the group.

In the embodiment of the application, the order system disassembles the inventory information into a form of three-level accounts so as to occupy different levels of accounts by the SKU.

The primary account is a warehouse general account, is the whole warehouse information of the SKU, and mainly comprises the following information: commodity ID, positive residual state, total physical inventory, total marketable inventory, total occupied inventory, etc.

The secondary account is a pool area type account, and besides the content of the primary account, the pool area type and the occupation data of the SKU in the operation process are newly added, wherein the pool area type is as follows: a goods preparation area, a picking area, a temporary storage area, a defective goods area, a differential stock area and the like.

The tertiary account is a warehouse inventory and the core expresses the number of SKUs on inventory levels in an inventory area.

In the embodiment of the application, the occupation actions of the primary account and the secondary account occur before the wave order task is established, so as to judge whether the order is out of stock or not and the occupation data among the same order system, transaction system and warehouse system. The step is mainly occupied according to a third-level account, and the inventory occupancy is mainly performed according to the grouping generated in the step 103 in two ways:

mode one: the order system obtains the stock distribution information of the stock of the SKU in the group by inquiring the third-level account information of the warehouse system, then determines the stock information of the stock occupied by the SKU in the group and which objects to be delivered in the group form a picking order through a path optimization rule, and then sends the stock information of the stock occupied by the SKU to the warehouse system for the warehouse system to take the action.

Mode two: the order system adopts an inventory clearing rule and a first-in first-out rule to inform a warehouse system of occupying inventory corresponding to the SKU in the group aiming at each group, and after the inventory is successfully occupied, the order system determines which objects to be delivered in the group form a picking list through a path optimization rule according to the occupied inventory position information, wherein the inventory clearing rule is that the inventory position corresponding to one SKU is occupied, and then the next inventory position corresponding to the SKU is occupied after the inventory position is occupied, so that the efficiency is higher. The first-in first-out rule is that in inventory management, the operation is performed according to the principle that the SKUs in the warehouse are occupied first when the SKUs are occupied according to the time sequence of the warehouse entry of the SKUs, and the timeliness is high.

Based on the two storage position occupation modes, the operation accuracy of the first mode is higher than that of the second mode, the picking path can be effectively reduced, the occupation efficiency of the second mode is higher, and the requirement of the storage occupation on efficiency in the period of increasing the number of orders such as double 11 can be met.

And 104, generating a picking order according to the warehouse position occupation information returned by the warehouse system.

In the embodiment of the application, after the warehouse system finishes occupying the warehouse position of at least one group, successful occupation information is sent to the order system, the order system generates a picking list according to the warehouse position information of the warehouse positions occupied by the SKUs in the group and the information of a picking list formed by the objects to be picked in the group, the content included in the picking list informs warehouse staff of the number of the SKUs included in the object to be picked and the positions to which the SKUs are respectively picked, and the warehouse staff can quickly and accurately perform the picking action according to the picking list.

In summary, according to the method for generating the picking order provided by the embodiment of the application, the wave order task aiming at the object to be delivered is generated; classifying objects to be delivered in the wave order task according to a preset picking strategy to obtain at least one group; then, according to at least one group, informing a warehouse system to occupy the inventory corresponding to the inventory units in the group; and finally, generating a picking order according to the bin occupation information returned by the warehouse system. According to the embodiment of the application, the wave order tasks are built by summarizing the objects to be delivered, and the objects to be delivered in the wave order tasks are classified according to the preset picking strategy of the warehouse system, so that at least one group is obtained, the aim of unifying the demands of adjacent orders for the same SKU is fulfilled, the warehouse system can carry out inventory occupation according to a clustering mode, a plurality of orders can be summarized for optimization, the aim is to occupy the same SKU in the same warehouse position as much as possible, the probability of occupying the same SKU in different warehouse positions for picking is reduced, the picking path length is reduced, and the picking efficiency is improved.

The following describes the interaction process of the order generation method in detail through the order system and the logistics system.

Referring to FIG. 3A, a flowchart illustrating specific steps of a pick order generation method of the present application may include the steps of:

in step 201, the order system receives an order.

In the online shopping process, the transaction system comprises an online shopping application facing a client and a merchant platform application facing a merchant, the client can browse on the online shopping application, when browsing the commodity of the cardiology instrument, the commodity ordering action can be carried out, a commodity order is generated, and the commodity order contains the SKU of the commodity and the required quantity of the SKU. In an embodiment of the present application, an order for the merchandise will be sent to the order system by the merchant platform application of the transaction system, a process known as "order taking".

In step 202, the order system sends the order to the warehouse system, informing the warehouse system to take the warehouse ledger occupation for the order.

In the embodiment of the application, after the order system takes the order, the order and the detail thereof are stored, and then a MetaQ message comprising the order and the detail thereof is sent to the warehouse system for the warehouse system to store the order and the detail thereof, wherein the process is the order taking of the warehouse system.

And 203, the warehouse system performs warehouse general account occupation aiming at the stock units in the order according to the order.

In the step, the warehouse system performs warehouse general account occupation aiming at stock units in the order, namely, occupies a primary account, and the purpose of occupying the primary account is to judge whether the general inventory of a SKU meets the requirement of the SKU in the order, if so, the occupation is successful, and if not, the transaction system is reminded of the backorder.

If the warehouse ledger occupancy fails, the warehouse system notifies the order system and the transaction system of the order out of stock, step 204.

In the embodiment of the application, if the warehouse general ledger fails to occupy, the warehouse is insufficient for the SKU, and the order system and the transaction system are informed that the SKU in the order is out of stock and needs to be supplemented, and when the supplementing is successful, the warehouse general ledger of the SKU can be continuously occupied.

If the warehouse ledger occupation is successful, the warehouse system broadcasts successful occupation information to the transaction system and the order system in step 205.

In the embodiment of the application, if the warehouse general ledger occupation is successful, the warehouse system broadcasts successful occupation information to the transaction system and the order system, so that the aim of unifying data among three systems is fulfilled, and the subsequent flow can be performed.

At step 206, the order system notifies the warehouse system to take inventory type occupancy for the order.

In the embodiment of the application, after the primary account is occupied by the warehouse system, the warehouse area type occupation, namely the occupation of the secondary account, can be performed, and the purpose of the warehouse system is to determine whether the SKU is in the picking area of the warehouse (the subsequent sorting action is the picking of the SKU in the picking area of the warehouse). It should be noted that, the occupation of the secondary account needs to be processed according to the order taking rule of the warehouse system, and the occupation of the secondary account and the occupation of the primary account in step 203 are uniformly scheduled according to the scheduling rule and the preset time, for example, the occupation actions of the primary account and the secondary account of 10 objects to be taken out of the warehouse are processed every 2 hours, so as to improve the occupation efficiency.

In step 207, the warehouse system performs warehouse style occupancy for the order.

Step 208, if the type of the warehouse area occupied by the order is a warehouse picking area, step 211 is executed.

In the embodiment of the application, the secondary account comprises the following storage area types: the stock area, the picking area, the temporary storage area, the defective goods area, the difference stock area and the like, and the picking operation can only pick SKUs in the picking area, so when the type of the stock area occupied by an order is the warehouse picking area, the stock of SKUs in the picking area is indicated to meet the requirement of the order, step 211 is executed at this time, according to a preset box cutting rule, the box cutting operation is carried out on stock units in the order by the order system, the action of a package object is obtained, and after the package is obtained, the establishment of a wave order task for the package can be carried out.

In 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 perform replenishment.

In this step, if the type of the stock area occupied by the order is a replenishment type area, it is indicated that the stock of SKUs in the sorting area cannot meet the demand of the order, and the replenishment system needs to be notified to replenish the stock area of SKUs at this time, where the replenishment type area may be a stock area, a temporary storage area, a defective product area, a differential stock area, and the like.

At step 210, the restocking system restocks the warehouse picking zone.

In an embodiment of the present application, the restocking system may specifically perform restocking on the warehouse sorting area, including: and dispatching a warehouse worker by the replenishment system to generate a replenishment bill for operation according to a certain rule and priority, and after the replenishment is completed, circularly carrying out secondary account occupation aiming at the SKU by the warehouse system until the occupation is successful.

Step 211, according to a preset box cutting rule, the order system performs box cutting operation on the stock quantity units in the order to acquire the package object.

In the embodiment of the application, the box cutting is a preprocessing action aiming at an order, and aims to aggregate SKUs in the order according to the dimensions of appearance and packaging attributes to obtain packages, and at the moment, the packages flow into a to-be-summarized package pool, and the later processing is aimed at the packages.

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

Commodity 1 size: 160 mm, 60 mm, 270 mm; number of: 3.

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

Commodity 3 size: 90 mm, 50 mm, 180 mm; number of: 2.

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

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

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

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

And then, according to the quantity and the structural specification of the commodities included in the order, the carton cutting determines and selects the No. 2 carton to package all the commodities in the order to obtain the package, so that the subsequent process can be performed according to the dimension of the package, and the subsequent picking, warehouse-out and distribution processes are convenient to perform.

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

Alternatively, a wave order task for the order may also be generated. At the moment, the box cutting action is not needed, and the flow of generating the picking list is simplified.

In the embodiment of the application, the object on which the wave order task is established can be an order or a package, and the embodiment of the application does not limit the order, and preferably, the wave order task aiming at the package object can be established, so that the subsequent process can be performed according to the dimension of the package, and the subsequent picking, warehouse-out and distribution processes are convenient to perform.

Optionally, step 212 further comprises sub-step 2121.

Sub-step 2121, adjusting a threshold of the number of wave-time tasks of the wave-time tasks according to a preset load balancing strategy, wherein the threshold of the number of wave-time tasks is the execution number of the wave-time tasks in a preset time.

In the embodiment of the application, the load balancing strategy means that the execution quantity of the wave number tasks in the preset time is required to meet the requirement of uniformity and no fluctuation, and because the working mode of the dispatching machine is similar to the process management of a computer, the dispatching machine is divided into a plurality of dispatching processes to execute the dispatching execution of the wave number tasks, for example, the maximum task wave number quantity operated by one dispatching process is set to be 5, therefore, a better wave number task quantity threshold can be obtained according to experiments, and the situation that the dispatching machine is blocked by the task wave number is avoided by setting the wave number task quantity threshold, so that the execution efficiency of the task wave number is improved.

And step 213, classifying objects to be taken out of the warehouse in the wave order task by the order system according to a preset picking strategy to obtain at least one group.

Step 213 may refer to the description of step 102, and is not described herein.

In step 214, the order system obtains inventory distribution information for the inventory locations storing the inventory units in the group.

In this step, the order system may obtain, in the warehouse system, library inventory distribution information of library bits of SKUs in the storage group, that is, a third level account, where the library inventory distribution information is library inventory distribution information updated after processing a previous wave task, and may be used as a basis for a subsequent inventory occupation process in the current wave task, so as to determine which library bit may occupy a corresponding SKU and which library bit may not occupy the corresponding SKU.

Step 215, according to the inventory distribution information of the stock, the order system determines the first order information of the group and the first stock information corresponding to the first order information by using a first path optimization rule; the first stock position information is the stock position information of the stock position occupied by the stock quantity unit in the first order picking information; the sum of the picking paths of the first pick order information is the shortest.

In the embodiment of the application, according to the inventory distribution information of the inventory levels, path optimization can be carried out on the occupied inventory levels of the SKUs through a first path optimization rule, first inventory level information and first order selection information are determined, the first inventory level information represents information of the inventory levels occupied by the SKUs in packages contained in a group, the inventory level information comprises physical position information of the inventory levels, the first order selection information comprises an order selection list composed of the packages in the group, and the requirements of the SKUs among orders are further optimized through the first path optimization rule, so that the SKUs with the same requirements can be classified into a class for inventory occupation, the occupation accuracy is improved, and the probability that the same SKU is occupied in different warehouse levels for picking is reduced.

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

Sub-step 2151, the order system reclusters the objects to be delivered in each group by using the first clustering algorithm model according to the inventory distribution information of the library positions.

In this step, there are various clustering algorithm models that can be used, and the present application is described by taking a Kmeans clustering model as an example. Specifically, the Kmeans algorithm is the most classical partition-based clustering method, and is one of ten major classical data mining algorithms. The basic idea of the Kmeans algorithm is: clustering is carried out by taking k points in space as centers, objects closest to the k points are classified, and the value of each clustering center is updated successively through an iterative method until the best clustering result is obtained.

For example: in a package group, the package includes SKUs of the following:

package 1: sku1, sku2, sku3;

package 2: sku2, sku3, sku4, sku8;

package 3: sku5, sku6, sku8;

package 4: sku7, sku8, sku10;

package 5: sku1, sku9.

The stock conditions are:

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。

from this, the vector of the parcel is expressed as:

(zone1,zone2,zone3,zone4,zone5,zone6,zone7)

according to the inventory distribution information of the library positions, if the corresponding library positions of the SKUs included in the package meet the occupation requirement, the dimension vector value is 1, otherwise, the dimension vector value is 0.

From this, the parcel vector is:

package 1: [1,1,1,1,0,0,0]

Package 2: [1,1,1,1,1,1,1]

Package 3: [1,0,0,0,1,1,1]

Package 4: [0,1,0,0,1,1,1]

Package 5: [1,1,1,0,0,0,1]

Assuming that the classification number of Kmeans classification is 2, namely two sheets of order are generated, and the convergence targets are as follows: the sum of the picking paths of the SKUs in the pick order is the shortest.

At this time, two cluster centroid points are randomly selected: the object similarity in the same cluster is higher according to the jacarod similarity between the package 1 and the package 2; and the object similarity in different clusters is smaller as a target. Steps 1 to 4 shown in fig. 3B are performed until the convergence result is obtained, and it should be noted that, for example, the jacarod distance between parcel 1 and parcel 2=4/7=0.57.

As can be seen from fig. 3B, finally, package 1 and package 5 are of one type, making up one pick sheet, and package 2, package 3, package 4 are of another type, making up another pick sheet. And picking corresponding SKUs in the bin with vector value 1 in the parcel vector respectively.

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

Sub-step 2152, using the clustering result as initial first order information, the order system optimizes the initial first order information by using a first genetic algorithm model, and obtains first order information with the shortest sum of picking paths.

In this step, the re-clustering result obtained in sub-step 2151 is used as the initial first order information, and the initial first order information may be further optimized by the first genetic algorithm model, so as to obtain a final preferred solution.

Specifically, the further optimization of the initial first pick order information by the first genetic algorithm model includes the following steps:

step S1, constructing an initial solution. Specifically, the solution of the problem is initially encoded, that is, the re-clustering result obtained in the sub-step 21121 is used as an initial solution, and is encoded into a vector form of 0-1 according to a rule, two initial solutions are generally required to be used as a parent and a parent, and the fitness of the parent and the parent is calculated, where the fitness is the sum of picking paths in a pick list.

Step S2, generating a new solution. The crossover strategy generally adopts truncation exchange, and the mutation strategy generally adopts fixed mutation probability or attenuation mutation probability.

Step S3, fine tuning to a feasible solution. The new solution generated in step S2 may not meet the constraint condition, so the new solution is domain-adjusted so that it meets the constraint, and at the same time, the adaptation of the new solution is good.

And S4, repeating the flow of the step 2-step 3, namely selecting the parent body and the parent body with the highest adaptability in the current sequence, and repeating the cross mutation flow until the sequence length is met.

And S5, outputting a solution with the maximum fitness, wherein the solution is the first order picking information with the shortest sum of picking paths.

In step 216, the order system sends the first bin information to the warehouse system, so that the warehouse system occupies the corresponding bin according to the first bin information.

In this step, the warehouse system performs the stock-position occupying action of the SKU for the first stock-position information by the first stock-position information, that is, the information that determines which stock position the SKU wrapped in the packet occupies.

Further, the warehouse system may also be notified of the occupancy of the warehouse picking zone with the warehouse bits based on the grouping.

In the embodiment of the application, the secondary account comprises the following storage area types: the stock area, the picking area, the temporary storage area, the defective goods area, the differential stock area and the like, and the picking operation can only pick the SKUs in the picking area, so that when the type of the stock area occupied by the order is the warehouse picking area, the stock of the SKUs in the picking area can meet the requirement of the order.

And step 217, the warehouse system occupies the corresponding library according to the first library information.

Step 218, when receiving the first place occupation message of the warehouse system, the order system generates a first order according to the first order information and the first place information corresponding to the first order information.

In the embodiment of the application, after the warehouse system occupies the corresponding warehouse location according to the first warehouse location information, successful occupation information is sent to the order system, the order system generates the first picking list according to the first warehouse location information of the warehouse location occupied by the SKUs in the group and the first picking list information of a picking list formed by the packages in the group, the first picking list comprises contents informing warehouse staff of which SKUs are included in the package and which warehouse location the SKUs are respectively picked, and the warehouse staff can rapidly and accurately perform the picking action according to the picking list.

In summary, in the method for generating a picking order according to the embodiment of the present application as shown in fig. 3A, an order system classifies objects to be picked in a task to obtain at least one group according to a preset picking policy, then the order system queries three-level account information of a warehouse system to obtain library inventory distribution information of library positions of SKUs in the group, determines library position information of library positions occupied by SKUs in the group and which objects to be picked in the group form a picking order according to a path optimization rule, and then sends the library position information of the library positions occupied by SKUs to the warehouse system for the warehouse system to perform an occupying action, and after the occupying is completed, the order system generates a first picking order.

The method for generating the picking order provided by the embodiment of the application generates the wave order task aiming at the object to be delivered; classifying objects to be delivered in the wave order task according to a preset picking strategy to obtain at least one group; then, according to at least one group, informing a warehouse system to occupy the inventory corresponding to the inventory units in the group; and finally, generating a picking order according to the bin occupation information returned by the warehouse system. According to the embodiment of the application, the wave order tasks are built by summarizing the objects to be delivered, and the objects to be delivered in the wave order tasks are classified according to the preset picking strategy of the warehouse system, so that at least one group is obtained, the aim of unifying the demands of adjacent orders for the same SKU is fulfilled, the warehouse system can carry out inventory occupation according to a clustering mode, a plurality of orders can be summarized for optimization, the aim is to occupy the same SKU in the same warehouse position as much as possible, the probability of occupying the same SKU in different warehouse positions for picking is reduced, the picking path length is reduced, and the picking efficiency is improved.

The following describes the interaction process of another order generation method through an order system and a logistics system in detail.

Referring to FIG. 4, a flowchart illustrating specific steps of another pick order generation method of the present application may specifically include the steps of:

in step 301, the order system receives an order.

Alternatively, step 301 may refer to the description of step 201 above, and will not be described herein.

In step 302, the order system sends the order to the warehouse system informing the warehouse system of the warehouse ledger occupation for the order.

Alternatively, step 302 may refer to the description of step 202 above, and will not be described herein.

And step 303, the warehouse system performs warehouse general account occupation aiming at the stock units in the order according to the order.

Optionally, step 303 may refer to the description of step 203, which is not described herein.

If the warehouse ledger occupation fails, the warehouse system notifies the order system and the transaction system of the order out of stock 304.

Alternatively, step 304 may refer to the description of step 204, which is not repeated herein.

If the warehouse ledger occupation is successful, the warehouse system broadcasts successful occupation information to the transaction system and the order system in step 305.

Alternatively, step 305 may refer to the description of step 205 above, and will not be described herein.

At step 306, the order system notifies the warehouse system to take inventory type occupancy for the order.

Optionally, step 306 may refer to the description of step 206 above, and is not described herein.

In step 307, the warehouse system performs a warehouse style occupation for the order.

Step 308, if the type of the warehouse area occupied by the order is a warehouse sorting area, step 311 is executed.

Alternatively, step 308 may refer to the description of step 208 above, and is not described herein.

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 perform replenishment.

Optionally, step 309 may refer to the description of step 209 above, which is not repeated here.

At step 310, the restocking system restocks the warehouse picking zone.

Alternatively, step 310 may refer to the description of step 210 above, and is not described herein.

Step 311, according to a preset box cutting rule, the order system performs box cutting operation on the stock quantity units in the order, and obtains the package object.

Alternatively, step 311 may refer to the description of step 211 above, and will not be described herein.

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

Alternatively, step 312 may refer to the description of step 212, which is not repeated herein.

Optionally, step 312 further comprises a sub-step 3121.

Sub-step 3121, adjusting a threshold of a number of wave-order tasks of the wave-order tasks according to a preset load balancing policy, where the threshold of the number of wave-order tasks is the number of execution of the wave-order tasks in a preset time.

Alternatively, step 3121 may refer to the description of step 2121, which is not repeated here.

Step 313, according to a preset picking strategy, the order system classifies the objects to be taken out of the warehouse in the wave order task to obtain at least one group.

Optionally, step 313 may refer to the description of step 213 above, and will not be described herein.

And step 314, the order system sends the group to the warehouse system so that the warehouse system occupies the inventory corresponding to the inventory units in the group according to the inventory clearing rule.

In the embodiment of the application, the order system adopts the inventory clearing rule and the first-in first-out rule to inform the warehouse system to occupy the inventory corresponding to the SKU in the group for each group, and after the inventory is successfully occupied, the path optimization rule is used for determining which packages in the group form a picking order according to the occupied inventory information, wherein the inventory clearing rule is that the inventory corresponding to the SKU is occupied for the next inventory corresponding to the SKU after the inventory is occupied for the inventory corresponding to the SKU, so that the efficiency is higher. The first-in first-out rule is that in inventory management, the operation is performed according to the principle that the SKUs in the warehouse are occupied first when the SKUs are occupied according to the time sequence of the warehouse entry of the SKUs, and the timeliness is high.

Step 315, the warehouse system occupies the inventory corresponding to the stock quantity units in the group according to the inventory clearing rule.

At step 316, the order system receives a second stock occupancy message returned by the warehouse system.

In this step, after the warehouse system completes occupying the inventory corresponding to the inventory units in the group according to the inventory clearing rule in step 314, the warehouse system sends successful occupying information to the order system, and the order system obtains second picking order information of the group according to the second bin position information of the bin positions occupied by SKUs in the group and the second path optimization rule.

Step 317, determining, by the order system, second order picking information of the group according to the second bin occupancy message using a second path optimization rule; the sum of the picking paths of the second pick order information is the shortest.

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

Sub-step 3171, the order system reclustering the objects to be delivered in each group by using the second clustering algorithm model according to the second bin occupancy message.

Unlike the example of step 2151 in the method for generating a pick order provided in fig. 3A, the inventory condition and parcel vector expression of SKUs in parcels in substep 3171 are determined by occupying SKUs in step 314 according to inventory clearing rules or first-in first-out rules, instead of determining SKUs according to the three-level account obtained by the query in step 2151, the second aggregation algorithm model may be calculated by using a Kmeans algorithm model, or may be calculated by using a cluster model with other similar functions, which is not limited in this application.

Sub-step 3172, using the clustering result as initial second order information, optimizing the initial second order information by the order system by using a second genetic algorithm model, and obtaining second order information with the shortest sum of the picking paths.

This step may refer to the description of the sub-step 2152 in the method for generating a pick order provided in fig. 3A, which is not described in detail in the embodiment of the present application.

It should be noted that, since the second bin occupancy message has been obtained according to the clear-bin rules in step 314, the result obtained in sub-step 3172 is the second pick order information with the shortest sum of the pick paths.

At step 318, the order system generates a second pick order from the second pick order information.

In the embodiment of the application, the second picking list comprises contents which inform warehouse staff of which SKUs are respectively included in the package, and which warehouse positions the SKUs occupy through the inventory cleaning rule, so that the warehouse staff can quickly and accurately perform the picking action according to the picking list.

In summary, according to another method for generating a picking order provided in fig. 4 of the embodiment of the present application, an order system classifies objects to be picked in a task to be picked according to a preset picking policy by generating the task to be picked, so as to obtain at least one group, then the order system informs a warehouse system to occupy the inventory corresponding to SKUs in the group by adopting a clear inventory rule and a first-in first-out rule for each group, after the occupancy is successful, it is determined by a path optimization rule which objects to be picked in the group form a picking order according to the occupied inventory information, wherein the clear inventory rule is that, for an inventory corresponding to a SKU, the occupancy of the next inventory corresponding to the SKU is performed after the inventory is occupied, and efficiency is high. The first-in first-out rule is that in inventory management, the operation is performed according to the principle that the SKUs in the warehouse are occupied first when the SKUs are occupied according to the time sequence of the warehouse entry of the SKUs, and the timeliness is high.

Based on the two kinds of bin occupation modes respectively provided in fig. 3A and fig. 4, the operation accuracy of the mode in fig. 3A is higher than that of the mode in fig. 4, the picking path can be effectively reduced, the occupation efficiency of the mode in fig. 4 is higher, the requirement of the bin occupation in the time of increasing the number of orders such as "double 11" for efficiency can be met, specifically, in the time of increasing the number of orders, the mode in fig. 4 can firstly carry out bin occupation on a large number of orders through a bin clearing rule, then the picking order information is obtained through simple path optimization, and the picking order is generated, so that the precision of the picking order on the bin occupation is not as high as that of the mode in fig. 3A, but the sorting efficiency of the picking order on the large number of orders is higher than that of the mode in fig. 3A, and in practical application, different bin occupation modes can be selected according to the requirement, and the application is not limited.

Referring to FIG. 5, a flowchart illustrating steps of another pick order generation method of the present application may specifically include the steps of:

step 401, generating a wave task aiming at an object to be delivered; the object to be ex-warehouse includes a stock quantity unit.

Step 401 may refer to the description of step 101, and is not repeated here.

Step 402, classifying the objects to be delivered in the wave order task according to a preset picking strategy to obtain at least one group.

Step 402 may refer to the description of step 102 above, and is not described herein.

Step 403, according to the grouping, occupying the inventory corresponding to the inventory units in the grouping.

For step 403, when the warehouse system and the order system may be aggregated into one overall system, step 403 may be performed according to the group, by using the overall system to occupy the inventory corresponding to the stock quantity unit in the group. In addition, the execution of step 403 may be completed by the warehouse system and the order system, and specifically, reference may be made to the description of step 403, which is not repeated herein.

Step 404, generating a picking order according to the occupied library positions.

For step 404, when the warehouse system and the order system may be aggregated into a total system, step 404 may generate a pick order from the total system based on the occupied inventory. In addition, the execution of step 404 may be completed by the warehouse system and the order system, and specifically, reference may be made to the description of step 404, which is not repeated herein.

It should be noted that, for simplicity of description, the method embodiments are shown as a series of acts, but it should be understood by those skilled in the art that the embodiments are not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred embodiments, and that the acts are not necessarily required by the embodiments of the application.

Referring to FIG. 6, a block diagram of a pick order generation device in one specific example of the application is shown, and may specifically include the following modules:

a first wave number establishing module 501, configured to generate a wave number task for an object to be delivered; the object to be ex-warehouse includes a stock quantity unit.

The first classification module 502 is configured to classify the objects to be delivered in the wave order task according to a preset picking policy, so as to obtain at least one group.

And the first inventory occupation module 503 is configured to notify the warehouse system to occupy the inventory corresponding to the inventory units in the group according to the group.

The first order generation module 504 is configured to generate an order according to the bin occupancy information returned by the warehouse system.

Referring to fig. 7, a specific block diagram of a pick order generation device in a specific example of the present application is shown, and may specifically include the following modules:

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

And 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:

and the first account occupation sub-module is used for informing the transaction system that the order is out of stock if the warehouse account occupation fails.

And the second general ledger occupation sub-module is used for broadcasting successful occupation information if the warehouse general ledger occupation is successful.

And a warehouse occupation module 603, configured to notify the warehouse system to perform warehouse type occupation for the order.

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

And the restocking module 605 is configured to notify the restocking system to restock if the type of the stock area occupied by the order is a restocking type area.

And the box cutting module 606 is used for carrying out box cutting operation on the stock quantity units in the order according to a preset box cutting rule to acquire the package object.

A first wave number establishing module 607, configured to generate a wave number task for an object to be delivered; the object to be ex-warehouse includes a stock quantity unit.

Optionally, the first wave number establishing module 607 includes:

and the order wave generation sub-module is used for generating wave tasks aiming at the orders.

And the package wave generation sub-module is used for generating wave tasks aiming at the package objects.

The load balancing module 608 is configured to adjust a threshold number of wave-order tasks of the wave-order tasks according to a preset load balancing policy, where the threshold number of wave-order tasks is the number of execution of the wave-order tasks in a preset time.

The first classification module 609 is configured to classify the objects to be delivered in the wave order task according to a preset picking policy, so as to obtain at least one group.

And the first inventory occupation module 610 is configured to notify the warehouse system to occupy the inventory corresponding to the inventory units in the group according to the group.

Optionally, the first inventory occupancy module 610 includes:

the acquisition sub-module is used for acquiring library position inventory distribution information of library positions for storing the stock quantity units in the group;

the first optimizing sub-module is used for determining first sorting order information of the group and first bin information corresponding to the first sorting order information by utilizing a first path optimizing rule according to the bin inventory distribution information; the first stock position information is the stock position information of the stock position occupied by the stock quantity unit in the first order picking information; the sum of the picking paths of the first pick order information is shortest;

and the second occupation sub-module is used for sending the group to the warehouse system so that the warehouse system occupies the inventory corresponding to the inventory units in the group according to the inventory clearing rule.

And the library bit occupation sub-module is used for informing a warehouse system to occupy library bits in the warehouse sorting area according to the grouping.

Optionally, the first optimizing sub-module includes:

the first clustering unit is used for reclustering the objects to be delivered in each group by utilizing the first clustering algorithm model according to the inventory distribution information of the library positions;

the first genetic optimization unit is used for taking the clustering result as initial first order information, optimizing the initial first order information by using a first genetic algorithm model, and acquiring first order information with the shortest sum of the order paths.

And the first occupation sub-module is used for sending the first library position information to the warehouse system so that the warehouse system occupies the corresponding library position according to the first library position information.

The first order generation module 611 is configured to generate an order according to the bin occupancy information returned by the warehouse system.

Optionally, the first pick order generation module 611 includes:

the first generation sub-module is used for generating a first picking order according to the first picking order information and the first bin position information corresponding to the first picking order information when receiving the first bin position occupation message of the warehouse system.

The receiving sub-module is used for receiving a second library bit occupation message returned by the warehouse system;

The second optimizing sub-module is used for determining second sorting order information of the group by utilizing a second path optimizing rule according to the second bin occupation message; the sum of the picking paths of the second pick order information is shortest;

optionally, the second optimizing sub-module includes:

the second clustering unit is used for reclustering the objects to be delivered in each group by utilizing the second clustering algorithm model according to the second library bit occupation message;

and the second genetic optimization unit is used for taking the clustering result as initial second order information, optimizing the initial second order information by using a second genetic algorithm model, and acquiring second order information with the shortest sum of the order paths.

And the second generation sub-module is used for generating a second picking order according to the second picking order information.

Referring to FIG. 8, there is shown a block diagram of another pick order generation device in one specific example of the present application, which may include the following modules in particular:

a second wave number establishing module 701, configured to generate a wave number task for an object to be delivered; the object to be delivered comprises a stock quantity unit;

the second classification module 702 is configured to classify objects to be taken out of the warehouse in the wave task according to a preset picking policy to obtain at least one group;

A second inventory occupation module 703, configured to occupy, according to the group, an inventory corresponding to the inventory units in the group;

and the second order generation module 704 is configured to generate an order according to the occupied bin.

In summary, the order generation device provided by the embodiment of the application generates the wave order task for the object to be delivered; classifying objects to be delivered in the wave order task according to a preset picking strategy to obtain at least one group; then, according to at least one group, informing a warehouse system to occupy the inventory corresponding to the inventory units in the group; and finally, generating a picking order according to the bin occupation information returned by the warehouse system. According to the embodiment of the application, the wave order tasks are built by summarizing the objects to be delivered, and the objects to be delivered in the wave order tasks are classified according to the preset picking strategy of the warehouse system, so that at least one group is obtained, the aim of unifying the demands of adjacent orders for the same SKU is fulfilled, the warehouse system can carry out inventory occupation according to a clustering mode, a plurality of orders can be summarized for optimization, the aim is to occupy the same SKU in the same warehouse position as much as possible, the probability of occupying the same SKU in different warehouse positions for picking is reduced, the picking path length is reduced, and the picking efficiency is improved.

For the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments for relevant points.

Fig. 9 is a schematic structural diagram of a server according to an embodiment of the present application. Referring to fig. 9, a server 800 may be used to implement the method of determining a wave order task provided in the above-described embodiment. The server 800 may vary considerably in configuration or performance and may include one or more central processing units (central processing units, CPUs) 822 (e.g., one or more processors) and memory 832, one or more storage media 830 (e.g., one or more mass storage devices) storing applications 842 or data 844. Wherein the memory 832 and the storage medium 830 may be transitory or persistent. The program stored in the storage medium 830 may include one or more modules (not shown), each of which may include a series of instruction operations on a server. Still further, the central processor 822 may be configured to communicate with the storage medium 830 to 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 supplies 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 OS XTM, unixTM, linuxTM, freeBSDTM, and the like. The central processor 822 may execute, among other things, the following instructions on the server 800:

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

acquiring library position inventory distribution information of library positions for storing the stock quantity units in the group;

determining first sorting order information of the group and first bin information corresponding to the first sorting order information by utilizing a first path optimization rule according to the bin inventory distribution information; the first stock position information is the stock position information of the stock position occupied by the stock quantity unit in the first order picking information; the sum of the picking paths of the first pick order information is shortest;

And sending the first bin information to the warehouse system so that the warehouse system occupies the corresponding bin according to the first bin information.

Optionally, the first path optimization rule includes a first clustering algorithm model and a first genetic algorithm model, and reclustering the objects to be delivered in each group by using the first clustering algorithm model according to the inventory distribution information of the library positions;

and taking the clustering result as initial first order information, optimizing the initial first order information by using a first genetic algorithm model, and obtaining first order information with the shortest sum of the order paths.

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

Optionally, the group is sent to the warehouse system, so that the warehouse system occupies the inventory corresponding to the inventory units in the group according to the inventory clearing rule.

Optionally, receiving a second bin occupation message returned by the warehouse system;

determining second order information of the group by using a second path optimization rule according to the second bin occupation message; the sum of the picking paths of the second pick order information is shortest;

And generating a second order according to the second order information.

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

reclustering the objects to be delivered in each group by using the second clustering algorithm model according to the second library position occupation message;

and taking the clustering result as initial second order information, and optimizing the initial second order information by using a second genetic algorithm model to obtain second order information with the shortest sum of the order paths.

Optionally, an order is received.

Optionally, a wave order task for the order is generated.

Optionally, according to a preset load balancing policy, adjusting a threshold value of the number of wave-order tasks of the wave-order tasks, where the threshold value of the number of wave-order tasks is the number of execution of the wave-order tasks in a preset time.

Optionally, according to a preset box cutting rule, box cutting operation is performed on the stock quantity units in the order, and the package object is obtained.

Optionally, generating a wave order task for the wrapped object.

Optionally, notifying the warehouse system to perform warehouse type occupancy for the order;

if the type of the warehouse area occupied by the order is a warehouse sorting area, executing the step of generating a wave task aiming at the object to be delivered;

And if the type of the stock area occupied by the order is a replenishment type area, notifying a replenishment system to replenish.

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

Optionally, notifying the warehouse system to perform warehouse ledger occupation for stock units in the order.

Optionally, if the warehouse ledger fails to occupy, notifying a transaction system that the order is out of stock.

Optionally, if the warehouse ledger occupies successfully, broadcasting successful occupancy information.

The present application provides an apparatus, 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 order generation method.

The present application also provides one or more machine-readable media having instructions stored thereon that, when executed by one or more processors, cause an apparatus to perform a pick order generation method.

The present application provides an apparatus, one or more machine-readable media having instructions stored thereon, which when executed by the one or more processors, cause the apparatus to perform another pick order generation method.

The present application also provides one or more machine-readable media having instructions stored thereon that, when executed by one or more processors, cause an apparatus to perform another pick order generation method.

In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described by differences from other embodiments, and identical and similar parts between the embodiments are all enough to be referred to each other.

It will be apparent to those skilled in the art that embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, 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. Furthermore, embodiments of the application may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations 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, which execute via the processor of the computer or other programmable data processing terminal device, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the scope of the embodiments of the application.

Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or terminal device comprising the element.

The above description of the method and apparatus for generating a picking order provided by the present application has described specific examples, which are only used to help understand the method and core idea of the present application; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.

Claims

1. A method of generating a pick order, comprising:

generating a picking order according to the warehouse position occupation information returned by the warehouse system;

the step of notifying a warehouse system to occupy the inventory corresponding to the stock quantity unit in the group according to the group comprises the following steps: determining the library position information of the library position of the stock quantity unit in the group, and informing the warehouse system to occupy the corresponding inventory of the stock quantity unit in the group.

2. The method of claim 1, wherein the step of notifying the warehouse system of occupancy of the inventory corresponding to the inventory units in the group based on the group comprises:

3. The method of claim 2, wherein the first path optimization rule comprises a first clustering algorithm model, a first genetic algorithm model; the step of determining the grouped first order information and the first bin information corresponding to the first order information by using a first path optimization rule according to the bin inventory distribution information comprises the following steps:

reclustering the objects to be delivered in each group by using the first clustering algorithm model according to the library stock distribution information;

4. A method according to claim 3, wherein the step of generating a pick order from the inventory occupancy information returned by the warehouse system comprises:

when a first bin occupation message of the warehouse system is received, a first picking order is generated according to the first picking order information and the first bin information corresponding to the first picking order information.

5. The method of claim 1, wherein the step of notifying the warehouse system of occupancy of the inventory corresponding to the inventory units in the group based on the group comprises:

and sending the group to the warehouse system so that the warehouse system occupies the inventory corresponding to the inventory units in the group according to the inventory clearing rule.

6. The method of claim 5, wherein the step of generating a pick order based on the inventory occupancy information returned by the warehouse system comprises:

receiving a second bin occupation message returned by the warehouse system;

and generating a second order according to the second order information.

7. The method of claim 6, wherein the second path optimization rule comprises a second generic algorithm model, a second genetic algorithm model; determining second order information of the group by using a second path optimization rule according to the second bin occupancy message, wherein the step comprises the following steps:

and taking the clustering result as initial second order information, optimizing the initial second order information by using the second genetic algorithm model, and obtaining second order information with the shortest sum of the order paths.

8. The method as recited in claim 1, further comprising:

an order is received.

9. The method of claim 8, wherein the step of generating a wave order task for an object to be ex-warehouse comprises:

generating a wave order task for the order.

10. The method as recited in claim 9, further comprising:

and adjusting the threshold value of the number of the wave-order tasks according to a preset load balancing strategy, wherein the threshold value of the number of the wave-order tasks is the execution number of the wave-order tasks in preset time.

11. The method as recited in claim 8, further comprising:

and carrying out box cutting operation on the stock units in the order according to a preset box cutting rule, and obtaining the package object.

12. The method of claim 11, wherein the step of generating a wave order task for an object to be ex-warehouse comprises:

Generating a wave order task for the wrapped object.

13. The method of claim 9, further comprising, prior to the step of generating the order-specific wave-order task:

notifying the warehouse system to perform warehouse type occupation for the order;

14. The method of claim 13, wherein the step of notifying a warehouse system of occupancy of inventory corresponding to the inventory units in the group based on the group comprises:

and notifying a warehouse system to occupy the warehouse sorting area according to the grouping.

15. The method as recited in claim 8, further comprising:

notifying the warehouse system to perform warehouse ledger occupation for the stock units in the order.

16. The method as recited in claim 15, further comprising:

and if the warehouse general ledger occupation fails, notifying a transaction system that the order is out of stock.

17. The method as recited in claim 15, further comprising:

and if the warehouse general ledger occupation is successful, broadcasting successful occupation information.

18. A method of generating a pick order, comprising:

generating a picking order according to the occupied library positions;

wherein, according to the grouping, occupying the inventory corresponding to the inventory unit in the grouping includes: determining the library position information of the library position of the stock quantity unit in the group, and informing a warehouse system to occupy the corresponding stock of the stock quantity unit in the group.

19. A pick order generation device, comprising:

the first picking order generation module is used for generating a picking order according to the warehouse position occupation information returned by the warehouse system;

the first inventory occupation module is specifically configured to determine inventory position information of an inventory position where the inventory unit is located in the group, and notify the warehouse system to occupy an inventory corresponding to the inventory unit in the group.

20. The apparatus of claim 19, wherein the first inventory occupancy module comprises:

21. The apparatus of claim 20, wherein the first path optimization rule comprises a first clustering algorithm model, a first genetic algorithm model; the first optimization sub-module comprises:

22. The apparatus of claim 21, wherein the first pick order generation module comprises:

23. The apparatus of claim 19, wherein the first inventory occupancy module comprises:

24. The apparatus of claim 23, wherein the first pick order generation module comprises:

25. The apparatus of claim 24, wherein the second optimization sub-module comprises:

the second clustering unit is used for reclustering the objects to be delivered in each group by using a second clustering algorithm model according to the second library bit occupation message;

26. The apparatus as recited in claim 19, further comprising:

and the order receiving module is used for receiving the order.

27. The apparatus of claim 26, wherein the first wave number establishment module comprises:

28. The apparatus as recited in claim 27, further comprising:

the load balancing module is used for adjusting the threshold value of the number of the wave-order tasks according to a preset load balancing strategy, wherein the threshold value of the number of the wave-order tasks is the execution number of the wave-order tasks in a preset time.

29. The apparatus as recited in claim 26, further comprising:

and the box cutting module is used for carrying out box cutting operation on the stock quantity units in the order according to a preset box cutting rule to obtain the package object.

30. The apparatus of claim 29, wherein the first wave number establishment module comprises:

31. The apparatus as recited in claim 27, further comprising:

the warehouse system is used for receiving the order from the warehouse system, and the warehouse system is used for receiving the order from the warehouse system;

the picking area occupation module is used for executing the step of generating the wave order task aiming at the object to be delivered if the type of the warehouse area occupied by the order is a warehouse picking area;

and the replenishment module is used for notifying the replenishment system to replenish if the type of the stock area occupied by the order is a replenishment type area.

32. The apparatus of claim 31, wherein the first inventory occupancy module comprises:

33. The apparatus as recited in claim 26, further comprising:

and the general ledger occupation module is used for informing the warehouse system of occupying the warehouse general ledger aiming at the order.

34. The apparatus as recited in claim 33, further comprising:

35. The apparatus as recited in claim 33, further comprising:

36. A pick order generation device, comprising:

the second picking order generation module is used for generating a picking order according to the occupied storage positions;

the second inventory occupation module is specifically configured to determine inventory position information of an inventory position where the inventory unit is located in the group, and notify a warehouse system to occupy an inventory corresponding to the inventory unit in the group.

37. A pick order generation device, comprising:

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 the method of any of claims 1-17.

38. One or more machine readable media having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform the method of any of claims 1-17.

39. A pick order generation device, comprising:

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 the method of claim 18.

40. One or more machine readable media having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform the method of claim 18.