WO2024011971A1

WO2024011971A1 - Order processing method and apparatus, and computer-readable storage medium

Info

Publication number: WO2024011971A1
Application number: PCT/CN2023/086799
Authority: WO
Inventors: 李双双; 夏春浩; 郭策; 商春鹏
Original assignee: 北京沃东天骏信息技术有限公司; 北京京东世纪贸易有限公司; 北京京东乾石科技有限公司
Priority date: 2022-07-11
Filing date: 2023-04-07
Publication date: 2024-01-18
Also published as: CN115147185A

Abstract

The present disclosure relates to the field of data processing. Disclosed are an order processing method and apparatus, and a computer-readable storage medium. The order processing method comprises: performing path planning according to reception addresses of orders in an order pool, so as to generate path aggregation orders corresponding to a path planning result; and generating one or more goods-picking aggregation orders according to the path aggregation orders. Provided in the embodiments of the present disclosure is an intelligent logistics solution. Path planning is performed by using reception addresses in orders, and the orders are aggregated by means of a path planning result, so as to generate path aggregation orders, such that subsequent sorting and distribution operations are performed according to the path aggregation orders.

Description

Order processing methods, devices and computer-readable storage media

Cross-references to related applications

This application is based on the application with CN application number 202210808960.5 and the filing date is July 11, 2022, and claims its priority. The disclosure content of the CN application is hereby incorporated into this application as a whole.

Technical field

The present disclosure relates to the field of data processing, and in particular to an order processing method, device and computer-readable storage medium.

Background technique

At present, the store's contract performance scope includes an area with the store as the center and a certain length (for example, 3 kilometers) as the radius. The store's contract performance scope is divided into multiple road areas according to neighborhoods or streets. In related technologies, before issuing a picking task, the store combines the received orders into a collection order based on the same expected delivery time and road area of the user. During production, goods are picked according to the collection order, and during distribution, goods are collected according to the collection order. It is expected that the work efficiency of production and distribution personnel can be improved through the collection order.

Contents of the invention

According to a first aspect of some embodiments of the present disclosure, an order processing method is provided, including: performing path planning according to the delivery address of the order in the order pool to generate a path collection order corresponding to the path planning result; and aggregating the order according to the path , generate one or more picking set orders.

In some embodiments, performing path planning based on the shipping address of the order in the order pool to generate a path set order corresponding to the path planning result includes: under the preset first constraint, based on the shipping address of the order in the order pool Perform path planning to generate a path collection order corresponding to the path planning result; where the first constraint includes the maximum order quantity, earliest delivery time, dispersion of delivery addresses, and number of inventory units of the orders involved in the path collection order At least one of the upper limit, whether the delivery address spans regions, the upper weight limit, the upper limit of the distance of the order, the delivery sequence, the time window of expected delivery, or whether it spans production waves.

In some embodiments, performing path planning based on the delivery address of the order in the order pool to generate a path set order corresponding to the path planning result includes: using a first algorithm to perform path planning on the delivery address of the order in the order pool to generate The path set order corresponding to the path planning result; wherein, the first algorithm includes: randomly selecting from the order pool The machine selects an order and inserts it into the path collection order, including: in the case of an existing path collection order, if a matching position can be found in the existing path collection order using the matching strategy, the randomly selected order is inserted into the matching position; And, if a matching position cannot be found in the existing route set order, or there is currently no route set order, the randomly selected order will be inserted into the new route set order; wherein, the above process is repeated to randomly select one from the order pool. Orders are inserted into the path collection order step until there are no orders in the order pool.

In some embodiments, performing path planning based on the delivery address of the order in the order pool to generate a path set order corresponding to the path planning result includes: using a second algorithm to perform path planning on the delivery address of the order in the order pool to generate The path set order corresponding to the path planning result; wherein, the second algorithm includes: dividing the orders in the order pool into seed orders and non-seed orders according to the classification rules; repeated execution: randomly selecting a seed order from multiple seed orders as the basic order , and use the matching strategy to select seed orders and non-seed orders that can be placed in the same path set order with the basic order to generate a path set order until multiple seed orders are processed.

In some embodiments, the order processing method further includes: when the route set order satisfies the second constraint, issuing the route set order at the issuance time of the route set order; or when the route set order does not satisfy the second constraint. If the conditions are met and the issuance time of the route set order is reached, the route set order is issued; where the issuance time of the route set order is determined based on the earliest issuance time of the orders in the route set order.

In some embodiments, route planning is performed based on the delivery addresses of orders in the order pool at a preset cycle.

In some embodiments, when the route set order does not satisfy the second constraint and the issuance time of the route set order has not yet been reached, the orders in the route set order participate in the route planning of the next cycle.

In some embodiments, the second constraint includes at least one of the following: the earliest production time of the route collection order is greater than the sum of the current time and preset parameters, where the earliest production time is the production time of each order in the route collection order the earliest time in the route collection order; the total number of orders in the route collection order is not within the preset range; or in the route collection order, the delivery time of the target category order is greater than the delivery time of the non-target category order.

In some embodiments, the order processing method further includes: for orders in the order pool that have not been added to the route set orders, when the order issuance time is currently reached, issue the order.

In some embodiments, the order processing method further includes: determining a time to add the generated order to the order pool based on the expected delivery time of the generated order.

In some embodiments, the order processing method further includes: in the case where a picking collection order is generated according to the route collection order, allocating all orders in the picked collection order to the same distribution unit for delivery; or, When multiple picking set orders are generated based on route set orders, multiple picking sets are processed. Orders in the picking set order in normal outbound status are assigned to the same delivery unit for delivery.

According to a second aspect of some embodiments of the present disclosure, an order processing device is provided, including: a route set order generation module configured to perform route planning based on the delivery address of the order in the order pool to generate a route planning result corresponding to The path collection order; the picking collection order generation module is configured to generate one or more picking collection orders based on the path collection order.

According to a third aspect of some embodiments of the present disclosure, an order processing device is provided, including: a memory; and a processor coupled to the memory, the processor being configured to execute any of the foregoing based on instructions stored in the memory. How to process orders.

According to a fourth aspect of some embodiments of the present disclosure, an order processing system is provided, including: any of the foregoing order processing devices; and an order pool, where the order pool is configured in a database.

In some embodiments, the order processing system further includes: a production subsystem configured to generate a sorting task according to the sorting collection order, and send the sorting task to the terminal device.

According to a fifth aspect of some embodiments of the present disclosure, there is provided a computer-readable storage medium on which a computer program is stored, wherein when the program is executed by a processor, any one of the foregoing order processing methods is implemented.

Other features and advantages of the present disclosure will become apparent from the following detailed description of exemplary embodiments of the present disclosure with reference to the accompanying drawings.

Description of drawings

In order to explain the embodiments of the present disclosure or the technical solutions in the prior art more clearly, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are only These are some embodiments of the present disclosure. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without exerting any creative effort.

Figure 1 shows a schematic flowchart of an order processing method according to some embodiments of the present disclosure.

2A and 2B are schematic diagrams of path collection orders according to some embodiments of the present disclosure.

3A and 3B are schematic diagrams of path set orders according to other embodiments of the present disclosure.

Figure 4 shows a schematic flowchart of a method for issuing a route collection order according to some embodiments of the present disclosure.

Figure 5 shows a schematic structural diagram of an order processing device according to some embodiments of the present disclosure.

Figure 6 shows a schematic structural diagram of an order processing system according to some embodiments of the present disclosure.

Figure 7 shows a schematic structural diagram of an order processing device according to other embodiments of the present disclosure.

FIG. 8 shows a schematic structural diagram of an order processing device according to further embodiments of the present disclosure.

Detailed ways

The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only some of the embodiments of the present disclosure, rather than all of the embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application or uses. Based on the embodiments in this disclosure, all other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the scope of protection of this disclosure.

The relative arrangement of components and steps, numerical expressions, and numerical values set forth in these examples do not limit the scope of the disclosure unless otherwise specifically stated.

At the same time, it should be understood that, for convenience of description, the dimensions of various parts shown in the drawings are not drawn according to actual proportional relationships.

Techniques, methods and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such techniques, methods and devices should be considered part of the authorized specification.

In all examples shown and discussed herein, any specific values are to be construed as illustrative only and not as limiting. Accordingly, other examples of the exemplary embodiments may have different values.

It should be noted that similar reference numerals and letters refer to similar items in the following figures, so that once an item is defined in one figure, it does not need further discussion in subsequent figures.

After analyzing the relevant technology, the inventor found that the orders participating in the order collection were all orders in the same time period, and the production time and delivery time were relatively concentrated, which could easily lead to the failure of the store's production and delivery to fulfill the contract. Moreover, the number of orders collected by the system cannot meet the order quantity requirements of delivery personnel for a single delivery. Delivery personnel need to manually wait for the orders to be consolidated, and then plan the delivery sequence according to the address, which affects delivery efficiency and user experience. Once a large number of orders are backlogged, a large amount of data will accumulate in the order, sorting, and outbound data systems, causing excessive pressure on the system and resulting in problems such as untimely response.

A technical problem to be solved by the embodiments of the present disclosure is: how to process orders to improve the operating efficiency and distribution efficiency of the data system.

Figure 1 shows a schematic flowchart of an order processing method according to some embodiments of the present disclosure. As shown in Figure 1, the order processing method in this embodiment includes steps S102 to S106.

In step S102, obtain the orders in the order pool.

In some embodiments, the order pool is implemented in the form of a database or data table. That is, orders added to the order pool are stored in a preset database or data table. In addition, you can also check the order corresponding to the order added to the order pool. The data entry adds the preset order pool ID. When an order is removed from the order pool, such as when the order is canceled or a production task has been released, the order will be deleted from the preset database or data table, or the preset order pool ID will be modified. If necessary, those skilled in the art can also implement it in other ways, which will not be described again here.

In some embodiments, the time to add the generated order to the order pool is determined based on the expected delivery time of the generated order. For example, if the expected delivery time of order 1 is a certain time period of the day, it will be added to the order pool after the order is generated; if the expected delivery time of order 2 is a certain time of the next day, it will be added at 0:00 the next day. to the order pool. Thus, the generated route order set has higher availability.

In some embodiments, orders are obtained from an order pool at a preset period. That is, the process of automatic order collection is triggered periodically.

In step S104, route planning is performed based on the delivery address of the order in the order pool to generate a route set order corresponding to the route planning result. The route collection order includes part or all of the information of the original order in the order pool, such as the consignee, delivery address, list of goods to be delivered, expected delivery time,

In some embodiments, it is indicated which orders are aggregated into the same path by adding path collection order identifiers to the orders involved in the generated path, or by adding these orders to a preset data table. In addition, a new data record can also be generated, which record corresponds to the generated route collection order, and the data records corresponding to the involved orders are associated in the data record, for example, using identification (ID) association. If necessary, those skilled in the art can also adopt other implementation methods, which will not be described again here.

In some embodiments, the orders participating in path planning in the order pool are for the same store, and the starting point and end point of the planned path are the same, that is, the delivery unit (such as a rider, a courier vehicle, etc.) starts from one store and travels to multiple locations. A user returns to the store after delivery. This enables single-point to multi-point distribution.

In some embodiments, under a preset first constraint, route planning is performed based on the delivery address of the order in the order pool to generate a route set order corresponding to the route planning result.

The first constraint can be set by the store or set by the system by default. In some embodiments, the first constraint includes the maximum order quantity of the orders involved in the route collection order, the earliest delivery time, the degree of dispersion of the delivery address, the upper limit of the number of SKUs (stock keeping units), and whether the delivery address crosses regions. , weight limit, order distance limit, delivery sequence, expected delivery time window or whether it spans at least one of production waves. Therefore, the result of decision-making path planning, that is, the result of order collection, can be determined from multiple dimensions such as global optimality, delivery capabilities of delivery personnel, and relief of pressure during peak hours.

The degree of dispersion of delivery addresses can be measured by the angle between different delivery addresses and shipping addresses (such as store addresses). The larger the angle is, the more dispersed the delivery users are; the smaller the angle is, the more concentrated the users are.

The delivery scope of the store can be divided into multiple road areas according to residential areas, streets, etc. Whether the delivery address spans zones refers to whether multiple delivery addresses involved in the same route belong to the same road zone.

The delivery sequence is determined, for example, by the sequence of expected delivery time windows in the user's order. For example, if user A's expected delivery time is 10:00-10:30, user B's expected delivery time is 10:15-10:45, and user C's expected delivery time is 10:30-11:00, then the priority is User A, User B, and User C are delivered in sequence, which not only conforms to the chronological order, but also makes the delivery more coherent.

When generating a path, it can be converted into a Vehicle Routing Problem (VRP) problem. Considering that during peak hours, the number of orders to be calculated is large, in some embodiments a heuristic algorithm is used to solve the problem to improve calculation efficiency.

In step S106, one or more picking collection orders are generated according to the route collection order. Without splitting the route set order, one picking set order is generated; without splitting the route set order, multiple picking set orders are generated.

In some embodiments, a data entry corresponding to the picking set order is generated, which includes information about the route set order, or is associated with a data entry corresponding to the route set order.

A picking set order includes one or more orders, and each picking set order corresponds to a picking task. A picking task can be completed by one picking unit (such as a picker, an automatic picking machine), or by multiple picking units. After the picking task is generated based on the picking set order, the picking task information can be sent to the terminal corresponding to the picking unit.

Whether to split the route collection order into multiple picking collection orders can be determined based on the store's configuration.

In some embodiments, when a picking set order is generated, that is, the route set order is not split, the store adopts a scenario of zone picking and sorting while picking. A route set order corresponds to a picking set order, and picking units in multiple partitions pick at the same time. Then, the goods are shipped out of the warehouse according to the picking collection order, and the goods shipped out of the warehouse are assigned to the same distribution unit for distribution.

In some embodiments, when multiple picking collection orders are generated, that is, route collection orders are split, the store can adopt an integrated production mode of sorting and packaging. Since the delivery time of different orders may vary, the orders that have been delivered can be batch calculated and allocated to distribution units in real time. If after splitting, some orders have outbound exceptions, only the orders in the picking collection orders that are in normal outbound status will be assigned to the same distribution unit for delivery.

The above embodiment uses the delivery address in the order to perform path planning, and aggregates the orders through the path planning results to generate a path collection order, so that subsequent sorting and delivery operations can be performed based on the path collection order. As a result, orders can be automatically collected, so that orders can be processed in a more timely manner as a whole, improving the operating efficiency and distribution efficiency of the data system.

Two path planning methods are exemplarily described below.

In some embodiments, the first algorithm is used to perform path planning on the delivery address of the order in the order pool to generate a path set order corresponding to the path planning result. The first algorithm includes: randomly selecting an order from the order pool; in the case of existing path collection orders, if the matching strategy can be used to find a matching position in the existing path collection orders, then insert the randomly selected order into the matching position; If a matching position cannot be found in the existing route collection order, or there is currently no route collection order, a randomly selected order will be inserted into the new route collection order; an order will be randomly selected from the order pool repeatedly until there is no order in the order pool. Until order.

For example, the order pool includes 3 orders, and the corresponding order numbers are {11, 24, 33}. There are currently two paths to collect orders, specifically: Collection Order One: 1-3-14-26, Collection Order Two: 5-2-7.

Randomly extract an order from the order pool, that is, order 11, and then determine whether there is a position that satisfies the first constraint and minimizes the increase in the VRP objective function value in set order one and set order two. If such a position exists, Then insert order 11 at this position. If there is no position in set order one and set order two that satisfies the first constraint and minimizes the increase in the VRP objective function value, then order 11 is inserted into a new set order.

In some embodiments, a second algorithm is used to perform path planning on the delivery address of the order in the order pool to generate a path set order corresponding to the path planning result. The second algorithm includes: dividing orders in the order pool into seed orders and non-seed orders according to classification rules; randomly selecting a seed order from multiple seed orders as a base order; using a matching strategy to select a seed order that can be placed on the same path as the base order Collect the seed orders and non-seed orders in the order to generate the path collection order; repeatedly randomly select a seed order from multiple seed orders as the base order until multiple seed orders are processed.

In some embodiments, after using the above-mentioned first algorithm or second algorithm to generate multiple route set orders, a first optimization process is also performed on the multiple route set orders to obtain optimized set orders.

For example, the first optimization process includes: first randomly selecting a predetermined number of path collection orders as the first collection orders to be processed, and then moving at least one order into the order pool in each first collection order to be processed, and then using the above The first algorithm processes all orders in the order pool.

In some embodiments, in order to ensure the stability of the optimization process, if there are only two orders in a certain set order, the set order is selected.

In the above first optimization process, by reorganizing the orders included in the collective order, it is possible to obtain Optimized collection orders.

As shown in Figure 2A, there are currently 3 paths to collect orders. The set order 21 includes 5 orders, the set order 22 includes 2 orders, and the set order 23 includes 3 orders.

As shown in FIG. 2B , through the above-described first optimization process, the orders included in the collective orders 21 and 22 are reorganized. In this case, the set order 21 includes 4 orders, the set order 22 includes 3 orders, and the set order 23 remains unchanged.

In some embodiments, after the first optimization process, a second optimization process can also be performed on multiple route set orders, so that the route set orders can be randomly optimized.

For example, the second optimization process includes: generating random numbers at a preset frequency, and if the random numbers are greater than the preset disturbance value, checking whether there is an independent seed order, where an independent seed order is a seed order that does not form a path set order with other orders.

If there is an independent seed order, the independent seed order is moved into the order pool, and a predetermined number of path collection orders that meet the preset conditions are randomly selected as the second pending collection order.

For example, the preset conditions include: the total number of orders in the second pending collection order is less than the preset quantity threshold. That is, the collection order with a smaller order quantity is selected as the second pending collection order.

Next, all orders in each second pending collection order are moved into the order pool. Finally, the second algorithm is used to process all orders in the order pool.

As shown in Figure 3A, there are currently 3 paths to collect orders. The collective order 31 includes 5 orders, the collective order 32 includes 2 orders, and the collective order 33 includes 3 orders. In addition, there is a seed order 30 that is not combined with other orders to form a collective order.

As shown in FIG. 3B , through the second optimization process, the seed order 30 forms a collective order 33 with an order originally included in the collective order 31 and an order originally included in the collective order 32 . Thus, the overall order collection rate can be effectively improved.

It should be noted that in Figure 3B, through the second optimization process, one order in the original set order 32 does not form a set order with other orders. Since the order is a non-seed order, the order can be returned to the order pool to participate in the next collective order generation, thereby increasing the probability of the overall order combination being successful.

In some embodiments, it may also be determined whether to adopt the generated route set order based on a preset second constraint. The following describes an embodiment of the route collection order issuance method of the present disclosure with reference to FIG. 4 .

Figure 4 shows a schematic flowchart of a method for issuing a route collection order according to some embodiments of the present disclosure. As shown in Figure 4, the route collection order issuing method in this embodiment includes steps S402 to S410.

In step S402, it is determined whether the route set order satisfies the second constraint condition. If satisfied, execute step S404; if not satisfied, execute step S406.

In some embodiments, the second constraint includes at least one of the following: the earliest production time of the route set order is greater than the sum of the current time and the preset parameters, where the earliest production time is the production time of each order in the route set order. The earliest time, the production time is determined based on the user's expected delivery time, for example; the total number of orders in the route set order is not within the preset range; or, in the route set order, the delivery time of the target category order is greater than the non-target category order delivery time, for example, catering orders need priority delivery.

In step S404, the path collection order is issued at the issuance time of the path collection order.

The issuance time of the route set order is determined based on the earliest issuance time of the orders in the route set order. Release refers to initiating the production process of an order.

In some embodiments, the delivery time of the route set order = (max[(start delivery time-download lead time-production time-in-transit time), current system time + processing time]-reservation time), max is Refers to the calculation of the maximum value. The reserved time is, for example, 2 minutes.

In step S406, it is determined whether the issuance time of the route collection order is currently reached. If yes, execute step S408; if not, execute step S410.

In step S408, a route collection order is issued.

For example, route collection orders are sent to the production system to generate pick collection orders.

In step S410, the orders in the route set orders participate in the route planning of the next cycle. Thus, a better result is obtained.

In some embodiments, for orders in the order pool that are not added to the route set orders, the order is issued when the order's issuance time is currently reached. In some embodiments, the delivery time of such an order = max [(start delivery time - delivery lead time - production time - transit time), current system time + processing time]. After such orders are issued individually, they can be consolidated and processed by the production system according to other methods.

Through the above embodiment, a more reasonable path collection order can be obtained on the basis of meeting the order production time limit task, thereby improving the system operation efficiency and distribution efficiency as a whole.

An embodiment of the order processing device of the present disclosure is described below with reference to FIG. 5 .

Figure 5 shows a schematic structural diagram of an order processing device according to some embodiments of the present disclosure. As shown in Figure 5, the order processing device 500 of this embodiment includes: a route collection order generation module 5100, which is configured to perform route planning based on the delivery address of the order in the order pool to generate a route collection order corresponding to the route planning result. ; The picking set order generation module 5200 is configured to assemble orders according to the path and generate one or more picking set orders. one.

In some embodiments, the route collection order generation module 5100 is further configured to perform route planning according to the delivery address of the order in the order pool under the preset first constraint condition to generate a route collection order corresponding to the route planning result; Among them, the first constraint includes the maximum order quantity of the orders involved in the route collection order, the earliest delivery time, the degree of dispersion of the delivery address, the upper limit of the number of inventory units, whether the delivery address crosses the area, the upper limit of weight, and the distance of the order. At least one of the upper limit, delivery sequence, desired delivery time window, or whether it spans production waves.

In some embodiments, the route set order generation module 5100 is further configured to use a first algorithm to perform route planning on the delivery address of the order in the order pool to generate a route set order corresponding to the route planning result; wherein the first algorithm includes : Randomly select an order from the order pool and insert it into the route set order, including: in the case of an existing route set order, if a matching position can be found in the existing route set order using the matching strategy, the randomly selected order will be The order is inserted into the matching position; and, if the matching position cannot be found in the existing path collection order, or there is currently no path collection order, the randomly selected order is inserted into the new path collection order; wherein, repeating the above process from the order An order is randomly selected from the pool and inserted into the path collection order step until there is no order in the order pool.

In some embodiments, the route set order generation module 5100 is further configured to use a second algorithm to perform route planning on the delivery address of the order in the order pool to generate a route set order corresponding to the route planning result; wherein the second algorithm includes : According to the classification rules, the orders in the order pool are divided into seed orders and non-seed orders; repeated execution: randomly select a seed order from multiple seed orders as the base order, and use the matching strategy to select a seed order that can be placed in the same place as the base order. Seed orders and non-seed orders in route set orders to generate route set orders until multiple seed orders are processed.

In some embodiments, the order processing device 500 further includes a issuing module 5300, configured to issue the route set order at the issuing time of the route set order if the route set order satisfies the second constraint; or in If the route set order does not satisfy the second constraint and the issuance time of the route set order is currently reached, the route set order is issued; where, the issuance time of the route set order is based on the earliest issuance of the order in the route set order. Time determined.

In some embodiments, the route collection order generation module 5100 is further configured to perform route planning based on the delivery addresses of the orders in the order pool at a preset cycle.

In some embodiments, the issuance module 5300 is further configured to issue orders in the path collection order if the path collection order does not satisfy the second constraint and the issuance time of the path collection order has not yet arrived. Participate in path planning for the next cycle.

In some embodiments, the issuing module 5300 is further configured to issue orders for orders in the order pool that are not added to the route set orders when the issuing time of the order currently arrives.

In some embodiments, the order processing device 500 further includes an order pool generation module 5400, configured to determine the time to add the generated order to the order pool according to the expected delivery time of the generated order.

In some embodiments, the order processing device 500 further includes: a delivery allocation module 5500, configured to allocate all orders in the picked collection order to the same order when a picking collection order is generated according to the route collection order. One distribution unit performs distribution; or, when multiple picking collection orders are generated based on route collection orders, the orders in the picking collection orders in the multiple picking collections that are in normal outbound status are assigned to the same distribution unit for delivery.

An embodiment of the order processing system of the present disclosure is described below with reference to FIG. 6 .

Figure 6 shows a schematic structural diagram of an order processing system according to some embodiments of the present disclosure. As shown in FIG. 6 , the processing system 60 of this embodiment includes an order processing device 610 and an order pool 620 . For the specific implementation of the order processing device 610, reference can be made to the order processing device 500, which will not be described again here. The order pool 620 is configured in the database.

In some embodiments, the processing system 60 further includes a production subsystem 630 configured to generate picking tasks according to the picking collection orders and send the picking tasks to the terminal equipment.

In some embodiments, the delivery allocation module in the order processing device described above can also be deployed in the production subsystem.

Figure 7 shows a schematic structural diagram of an order processing device according to other embodiments of the present disclosure. As shown in Figure 7, the order processing device 70 of this embodiment includes: a memory 710 and a processor 720 coupled to the memory 710. The processor 720 is configured to execute any of the foregoing based on instructions stored in the memory 710. Order processing method in the embodiment.

The memory 710 may include, for example, system memory, fixed non-volatile storage media, etc. System memory stores, for example, operating systems, applications, boot loaders, and other programs.

FIG. 8 shows a schematic structural diagram of an order processing device according to further embodiments of the present disclosure. As shown in Figure 8 As shown, the order processing device 80 in this embodiment includes: a memory 810 and a processor 820, and may also include an input and output interface 830, a network interface 840, a storage interface 8500, etc. These interfaces 830, 840, 8500, the memory 810 and the processor 820 may be connected through a bus 860, for example. Among them, the input and output interface 830 provides a connection interface for input and output devices such as a monitor, mouse, keyboard, and touch screen. Network interface 840 provides a connection interface for various networked devices. The storage interface 8500 provides a connection interface for external storage devices such as SD cards and USB flash drives.

Embodiments of the present disclosure also provide a computer-readable storage medium on which a computer program is stored, which is characterized in that when the program is executed by a processor, any one of the aforementioned order processing methods is implemented.

Those skilled in the art will appreciate that embodiments of the present disclosure may be provided as methods, systems, or computer program products. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment that combines software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk memory, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein. .

The disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes 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 device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce a use A device for implementing the functions specified in one process or processes of the flowchart and/or one block or blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory that causes a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction means, the instructions The device implements the functions specified in a process or processes of the flowchart and/or a block or blocks of the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device, causing a series of operating steps to be performed on the computer or other programmable device to produce computer-implemented processing, thereby executing on the computer or other programmable device. Instructions provide steps for implementing the functions specified in a process or processes of a flowchart diagram and/or a block or blocks of a block diagram.

The above are only preferred embodiments of the present disclosure and are not intended to limit the present disclosure. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present disclosure shall be included in the protection of the present disclosure. within the range.

Claims

An order processing method, including:

Perform route planning based on the delivery addresses of orders in the order pool to generate route collection orders corresponding to the route planning results;

One or more picking collection orders are generated according to the path collection order.
The processing method according to claim 1, wherein said performing path planning according to the delivery address of the order in the order pool to generate a path set order corresponding to the path planning result includes:

Under the preset first constraint, route planning is performed based on the delivery address of the order in the order pool to generate a route set order corresponding to the route planning result;

Among them, the first constraint includes the maximum order quantity of the orders involved in the route collection order, the earliest delivery time, the degree of dispersion of the delivery address, the upper limit of the number of inventory units, whether the delivery address crosses the area, the upper weight limit, the order At least one of the distance limit, delivery sequence, expected delivery time window, or whether it spans production waves.
The processing method according to claim 1, wherein said performing path planning according to the delivery address of the order in the order pool to generate a path set order corresponding to the path planning result includes:

Use the first algorithm to perform path planning on the delivery address of the order in the order pool to generate a path set order corresponding to the path planning result;

Wherein, the first algorithm includes:

An order is randomly selected from the order pool and inserted into the path collection of orders, including:

In the case of an existing path collection order, if a matching position can be found in the existing path collection order using a matching strategy, a randomly selected order will be inserted into the matching position; and

If a matching position cannot be found in the existing route collection order, or there is currently no route collection order, the randomly selected order will be inserted into the new route collection order;

The step of randomly selecting an order from the order pool and inserting it into the path collection order is repeated until there is no order in the order pool.
The processing method according to claim 1, wherein the processing is performed according to the delivery address of the order in the order pool. Perform path planning to generate path collection orders corresponding to the path planning results, including:

Use the second algorithm to perform path planning on the delivery address of the order in the order pool to generate a path set order corresponding to the path planning result;

Wherein, the second algorithm includes:

Orders in the order pool are divided into seed orders and non-seed orders according to classification rules;

Repeat:

Randomly select one seed order from the plurality of seed orders as the base order, and

Use the matching strategy to select seed orders and non-seed orders that can be placed in the same path set order as the basic order to generate a path set order,

Until the multiple seed orders are processed.
The processing method according to any one of claims 1 to 4, further comprising:

If the route set order satisfies the second constraint, issue the route set order at the issuance time of the route set order; or

If the route set order does not satisfy the second constraint and the issuance time of the route set order is currently reached, issue the route set order;

Wherein, the issuance time of the route set order is determined based on the earliest issuance time of the orders in the route set order.
The processing method according to any one of claims 1 to 4, wherein path planning is performed based on the delivery address of the order in the order pool at a preset cycle.
The processing method according to any one of claims 1 to 4, wherein when the path collection order does not satisfy the second constraint and the issuance time of the path collection order has not yet arrived, the The orders in the path set order participate in the path planning of the next cycle.
The processing method according to claim 5 or 7, wherein the second constraint condition includes at least one of the following:

The earliest production time of the route set order is greater than the sum of the current time and preset parameters, wherein the earliest production time is the earliest time among the production times of each order in the route set order;

The total number of orders in the route set order is not within the preset range; or

Among the route set orders, the delivery time of orders of the target category is greater than the delivery time of orders of non-target categories.
The processing method according to any one of claims 1 to 4, further comprising:

For orders in the order pool that are not added to the route set orders, when the issuance time of the order is currently reached, the order is issued.
The processing method according to any one of claims 1 to 4, further comprising:

The time to add the generated order to the order pool is determined based on the expected delivery time of the generated order.
The processing method according to any one of claims 1 to 4, further comprising:

When a picking set order is generated based on the route set order, all orders in the picked set set order are assigned to the same delivery unit for delivery; or,

When multiple picking set orders are generated based on the path set order, orders in the picking set orders in the normal outbound state among the multiple picking sets are assigned to the same delivery unit for delivery.
An order processing device, including:

The route collection order generation module is configured to perform route planning based on the delivery address of the order in the order pool to generate a route collection order corresponding to the route planning result;

A picking collection order generating module is configured to generate one or more picking collection orders according to the path collection order.
An order processing device, including:

memory; and

A processor coupled to the memory, the processor being configured to execute the order processing method according to any one of claims 1 to 11 based on instructions stored in the memory.
An order processing system, including:

The order processing device according to claim 12 or 13; and

Order pool, the order pool is configured in the database.
The processing system of claim 14, further comprising:

The production subsystem is configured to generate a sorting task according to the sorting collection order, and send the sorting task to the terminal device.
A computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the order processing method described in any one of claims 1 to 11 is implemented.
A computer program consisting of:

Instructions, which when executed by a processor cause the processor to execute the order processing method according to any one of claims 1 to 11.