HK1237504B - Method and device for processing order - Google Patents

Description

Order processing method and apparatus

Technical Field

This application relates to the field of computer technology, specifically to the field of Internet technology, and in particular to order processing methods and apparatus.

Background Technology

With the rapid development of e-commerce, the volume of goods leaving the warehouse is increasing dramatically. Typically, the same item is stored in more than one storage box in the warehouse. With current technology, it is often difficult to efficiently determine the appropriate storage box for shipment from multiple boxes. Therefore, improving the efficiency of goods leaving the warehouse is an urgent problem to be solved.

Summary of the Invention

The purpose of this application is to provide an improved order processing method and apparatus to solve the technical problems mentioned in the background section above.

In a first aspect, embodiments of this application provide an order processing method, which includes: extracting item information of items to be shipped from an order to be processed; obtaining storage location information of at least one storage box storing the items to be shipped in a designated warehouse from a correspondence table between item information and storage location information; using a multi-objective genetic algorithm, selecting a storage box as the shipping storage box from at least one storage box according to the obtained storage location information and multiple preset objectives; determining the storage location information of the shipping storage box, determining the shipping device of the shipping storage box according to the preset correspondence between storage location information and transportation device, and determining the shipping device of the shipping storage box as the target transportation device; and sending a transportation instruction to the target transportation device so that the target transportation device transports the shipping storage box to a designated location.

In some embodiments, after sending a transport instruction to a target transport device to transport the outbound storage box to a designated location, the method further includes: obtaining a processing status list of storage boxes to be returned to the warehouse, the processing status list indicating the processing status of the storage boxes to be returned to the warehouse; if there is information on unprocessed storage boxes in the processing status list, then, based on multiple specified targets, using a multi-objective genetic algorithm that takes the transport frequency of unprocessed storage boxes within a specified historical time period as a parameter, determining the target storage location of the unprocessed storage boxes to be returned in the warehouse; and sending a return instruction to a specified transport device to transport the unprocessed storage boxes to the target storage location.

In some embodiments, before extracting the item information of the items to be shipped recorded in the pending orders, the method further includes: obtaining an order set processing status list, which is used to indicate the processing status of an order set consisting of orders; determining the number of order sets being processed based on the order set processing status list; if the number is less than a preset threshold, selecting an order set from at least one pending order set in a preset order, and taking the orders in the selected order set as pending orders.

In some embodiments, the transport device is a shuttle.

In some embodiments, different storage boxes are stored in different storage locations on the shelves, and transport channels for items are provided between adjacent shelves on the same floor; and a number of preset objectives include one of the following: minimizing the number of outbound storage boxes, minimizing the difference in the number of storage boxes transported on each transport channel, and minimizing the sum of the times for each outbound storage box to reach the designated location.

Secondly, this application provides an order processing apparatus, comprising: an extraction unit configured to extract item information of items to be shipped from an order to be processed; an acquisition unit configured to acquire, from a correspondence table of item information and storage location information, storage location information of at least one storage box storing the items to be shipped in a designated warehouse; a selection unit configured to use a multi-objective genetic algorithm to select a storage box as a shipping storage box from at least one storage box based on the acquired storage location information and multiple preset objectives; a determination unit configured to determine the storage location information of the shipping storage box, determine the shipping device of the shipping storage box based on a preset correspondence between storage location information and a transportation device, and determine the shipping device of the shipping storage box as a target transportation device; and a transportation unit configured to send a transportation instruction to the target transportation device so that the target transportation device transports the shipping storage box to a designated location.

In some embodiments, the apparatus further includes: a list acquisition unit configured to acquire a list of processing statuses of storage boxes to be returned to the warehouse, the list indicating the processing status of the storage boxes to be returned; a target determination unit configured to, if there is information on unprocessed storage boxes in the processing status list, determine the target storage location of the unprocessed storage boxes in the warehouse based on multiple specified targets using a multi-objective genetic algorithm that takes the transportation frequency of the unprocessed storage boxes in a specified historical time period as a parameter; and a sending unit configured to send a return instruction to a specified transportation device to transport the unprocessed storage boxes to the target storage location.

In some embodiments, the apparatus further includes: a status acquisition unit configured to acquire an order set processing status list, the order set processing status list indicating the processing status of an order set consisting of orders; a quantity determination unit configured to determine the quantity of order sets being processed based on the order set processing status list; and a selection unit configured to select an order set from at least one order set to be processed in a preset order if the quantity is less than a preset threshold, and to take the orders in the selected order set as orders to be processed.

In some embodiments, different storage boxes are stored in different storage locations on the shelves, and transport channels for items are provided between adjacent shelves on the same floor; and a number of preset objectives include one of the following: minimizing the number of outbound storage boxes, minimizing the difference in the number of storage boxes transported on each transport channel, and minimizing the sum of the times for each outbound storage box to reach the designated location.

The order processing method and apparatus provided in this application embodiment extract the item information of the items to be shipped from the order to be processed, obtain the storage location information of at least one storage box storing the items to be shipped in a designated warehouse from a specified correspondence table of item information and storage location information, and then use a multi-objective genetic algorithm to select a storage box as the shipping storage box from at least one storage box according to multiple preset objectives. Then, determine the storage location information of the shipping storage box, determine the shipping device of the shipping storage box according to the preset correspondence between storage location information and transportation device, and determine the shipping device of the shipping storage box as the target shipping device. Finally, send a transportation instruction to the target shipping device so that the target shipping device transports the shipping storage box to the designated location. This application embodiment uses a multi-objective genetic algorithm to determine the shipping storage box, thereby improving the shipping efficiency of items.

Attached Figure Description

Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

Figure 1 is an exemplary system architecture diagram in which this application can be applied;

Figure 2 is a flowchart of an embodiment of the order processing method according to this application;

Figure 3 is a schematic diagram of an application scenario of the order processing method according to this application;

Figure 4 is a flowchart of yet another embodiment of the order processing method according to this application;

Figure 5 is a schematic diagram of the structure of an embodiment of the order processing apparatus according to this application;

Figure 6 is a schematic diagram of the structure of a computer system suitable for implementing the server of the present application embodiments.

Detailed Implementation

The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

Figure 1 illustrates an exemplary system architecture 100 of an embodiment of the order processing method or order processing apparatus to which the present application may be applied.

As shown in Figure 1, the system architecture 100 may include terminal devices 101, 102, and 103, a network 104, and a server 105. The network 104 serves as the medium for providing communication links between the terminal devices 101, 102, and 103 and the server 105. The network 104 may include various connection types, such as wired or wireless communication links or fiber optic cables, etc.

Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as shopping applications, search applications, instant messaging tools, email clients, social media platform software, etc.

Terminal devices 101, 102, and 103 can be various electronic devices with displays that support online shopping, including but not limited to smartphones, tablets, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III), MP4 players (Moving Picture Experts Group Audio Layer IV), laptops, and desktop computers, etc.

Server 105 can be an order processing server for processing orders, which may be orders generated by users purchasing items using shopping applications on terminal devices 101, 102, and 103. The order processing server can analyze and process the storage information of the items in the order and feed the processing results back to the terminal devices.

It should be noted that the order processing method provided in this application embodiment is generally executed by server 105, and correspondingly, the order processing device is generally set in server 105.

It should be understood that the number of terminal devices, networks, and servers shown in Figure 1 is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

Referring again to Figure 2, a flow 200 of an embodiment of the order processing method according to this application is shown. The order processing method includes the following steps:

Step 201: Extract the item information of the items to be shipped from the orders to be processed.

In this embodiment, the electronic device (e.g., the server shown in Figure 1) on which the order processing method runs can retrieve orders to be processed from a local database (or memory space) or from a terminal device. The order records the item information of the items to be shipped, and this item information can be extracted.

Items awaiting shipment are those ready to be dispatched. The aforementioned electronic equipment can process orders that record item information to ensure the smooth dispatch of these items. An order may indicate one or more items awaiting shipment. Item information refers to information related to the item; specifically, it may include the item's name, specifications, quantity, etc.

Step 202: Obtain the storage location information of at least one storage box storing items to be shipped out in the designated warehouse from the correspondence table between item information and storage location information.

In this embodiment, the local database of the aforementioned electronic device can store a mapping table between item information and storage location information, and this mapping table is updated in real time. In the warehouse, there can be a large number of storage locations, which are used to store storage boxes containing items. The same item can be placed in one or more storage boxes. The aforementioned electronic device can obtain the storage location information of at least one storage box storing items by looking up the mapping table.

Storage location information indicates the location of a storage location, and may specifically include the column number, floor height, and whether it has double depth, etc. A string of numbers can be used to represent the storage location information.

The aforementioned correspondence table records the item information stored in each storage box, as well as the storage location information for that storage box. Typically, each item is stored in multiple storage boxes; therefore, by using the item information of one item, one can find the storage location information corresponding to each of the multiple storage boxes storing that item.

Step 203: Using a multi-objective genetic algorithm, select a storage box from at least one storage box as the outbound storage box based on the obtained storage location information and multiple preset objectives.

In this embodiment, after obtaining the storage location information of at least one storage box, the aforementioned electronic device can use a multi-objective genetic algorithm to select one storage box from the at least one storage box. Multiple objectives to be achieved by the algorithm can be preset. After setting the multiple objectives, the storage location information can be used as parameters of the genetic algorithm to calculate the optimal offspring storage box.

Multi-objective genetic algorithms are a method that searches for optimal solutions by simulating the natural evolutionary process to achieve multiple objectives. Specifically, to perform a multi-objective genetic algorithm operation, multiple objectives are first determined. For example, one objective could be to minimize the outbound transportation time of storage boxes. Initial storage boxes can be randomly selected, and after multiple iterations, the optimal offspring storage boxes are obtained. The optimal offspring storage box is then determined as the outbound storage box for the item.

In some optional implementations of this embodiment, different storage boxes are stored in different storage locations on the shelves, and transport channels for items are set between adjacent shelves on the same floor; and multiple preset objectives include one of the following: minimizing the number of outbound storage boxes, minimizing the difference in the number of storage boxes transported on each transport channel, and minimizing the sum of the times for each outbound storage box to reach the designated location.

The warehouse contains multiple shelves arranged vertically with numerous tiers, each containing multiple storage spaces. Storage boxes are paired with storage spaces, with different boxes placed in different locations. A transport aisle is established between every two adjacent shelves on the same tier, allowing transport devices to move and move goods within the aisles.

When transporting the same amount of goods, transporting as few outbound storage boxes as possible can reduce outbound time and improve outbound efficiency. Simultaneously, minimizing the difference in the number of storage boxes being transported in each transport aisle—that is, ensuring a uniform number of storage boxes across all aisles—prevents storage boxes from accumulating in the aisles and slowing down the outbound process. Ultimately, minimizing the sum of the times each outbound storage box takes to reach its designated location directly improves outbound efficiency.

Weights can be assigned to the aforementioned multiple objectives to perform multi-objective genetic algorithm calculations. The specific calculation methods are common techniques used by those skilled in the art and will not be elaborated upon here.

It should be noted that the three preset objectives mentioned above (minimizing the number of outbound storage boxes, minimizing the difference in the number of storage boxes transported on each transportation channel, and minimizing the sum of the times for each outbound storage box to reach the designated location) can all be used as multiple preset objectives. Alternatively, any combination of any two objectives can be used as multiple objectives. Furthermore, other objectives can be added based on these three objectives.

Using appropriate tools for computation can improve computational efficiency. Specifically, multi-objective genetic algorithms can be performed using specified object-oriented programming language development tools, such as IntelliJ IDEA. IntelliJ IDEA is a Java language integrated development environment (IDE) with excellent features in areas such as intelligent code assistance, code auto-completion, refactoring, J2EE support, various version control tools (git, svn, github, etc.), JUnit, CVS integration, code analysis, and innovative GUI design.

Step 204: Determine the storage location information of the outbound storage box. Based on the preset correspondence between the storage location information and the transportation device, determine the transportation device of the outbound storage box and designate the transportation device of the outbound storage box as the target transportation device.

In this embodiment, the aforementioned electronic device can determine the storage location information of the outgoing storage box from the acquired storage location information. In a warehouse, a transport device is a device capable of transporting goods. Each storage box in a storage location is transported by a corresponding transport device. By obtaining the correspondence between storage location information and transport devices, the transport device for the outgoing storage box can be determined using the storage location information of the outgoing storage box. The determined transport device can then be designated as the target transport device.

In some optional implementations of this embodiment, the transport device is a shuttle.

A shuttle is a transport vehicle that can travel between shelves. One shuttle can be configured on each shelf level. Therefore, one shuttle can correspond to one storage location on the same shelf level. Of course, multiple shuttles can be configured on one shelf level, or one shuttle can be configured across multiple floors.

Step 205: Send a transport instruction to the target transport device so that the target transport device transports the outbound storage box to the designated location.

In this embodiment, the aforementioned electronic device can send a transportation instruction to the determined target transportation device. This transportation instruction instructs the target transportation device to perform transportation, and may include the storage location information of the outgoing storage box, as well as the destination of the transportation. After receiving the transportation instruction, the target transportation device transports the outgoing storage box to the designated location.

The designated location can be any geographical location reachable by the target transport device. The transport device moves the outbound storage box to the designated location, thus completing one step of the outbound process.

Referring again to Figure 3, which is a schematic diagram of an application scenario of the order processing method according to this embodiment, in the application scenario of Figure 3, the order processing server extracts the item information of the item "ball" to be shipped from the order to be processed recorded in the local database. Then, the order processing server can obtain the storage location information of at least one storage box storing the item "ball" in the designated warehouse from the correspondence table between item information and storage location information. Then, the server uses a multi-objective genetic algorithm to select a storage box as the shipping storage box from at least one storage box according to the obtained storage location information and multiple preset objectives. Then, the server determines the storage location information of the shipping storage box, and determines the shipping device of the shipping storage box according to the correspondence between the preset storage location information and the transportation device, and determines the shipping device of the shipping storage box as the target shipping device. Finally, the server sends a transportation instruction to the target shipping device so that the target shipping device transports the shipping storage box to the designated location.

The method provided in the above embodiments of this application utilizes a multi-objective genetic algorithm to determine the outbound storage box, thereby improving the outbound efficiency of items.

Referring further to Figure 4, a flow 400 of another embodiment of the order processing method is shown. Flow 400 of this order processing method includes the following steps:

Step 401: Obtain the order collection processing status list.

In this embodiment, the order set processing status list is used to indicate the processing status of an order set consisting of orders. Considering the limited processing capacity of the server, in order to ensure that orders are processed normally, i.e., to prevent the server from crashing or experiencing other problems due to overload, it is necessary to obtain the processing status of the orders to determine the number of orders being processed. Therefore, the server obtains the order set processing status list, which records the processing status of the order set consisting of orders.

In practice, an order set can include one or more orders, which are orders that have not yet been processed for shipment. The processing status of an order set can include three states: unprocessed, being processed, and processed.

Step 402: Determine the number of order sets currently being processed based on the order set processing status list.

In this embodiment, since the order set processing status list can indicate the processing status of the order set, the server can directly determine how many order sets are in the processing state from the order set processing status list.

Step 403: If the quantity is less than a preset threshold, select an order set from at least one order set to be processed according to a preset order, and take the orders in the selected order set as orders to be processed.

In this embodiment, a quantity threshold can be preset for the set of orders being processed. If it is determined that the number of orders being processed is less than the preset threshold, the server itself still has processing capacity and can select an order set from at least one order set according to a preset selection order, and treat the orders in the selected order set as orders to be processed.

For example, the preset threshold is 3, meaning the server can handle a maximum of 3 order sets. If the order set processing status list shows that 2 order sets are currently being processed, then one order set can be selected from the multiple order sets for outbound processing.

The preset order can be random or the time order in which the order set is generated, etc.

Step 404: Extract the item information of the items to be shipped from the pending orders.

In this embodiment, the server can retrieve pending orders from a local database (or memory space) or from a terminal device. The orders record item information for the items to be shipped, and the server extracts this item information.

Step 405: Obtain the storage location information of at least one storage box storing items to be shipped out in the designated warehouse from the correspondence table between item information and storage location information.

In this embodiment, the local database of the aforementioned server can store a mapping table between item information and storage location information, and this mapping table is updated in real time. A large number of storage locations can be set up in the warehouse, and these locations are used to store storage boxes containing items. The same item can be placed in one or more storage boxes. The aforementioned server can obtain the storage location information of at least one storage box storing an item by looking up the mapping table; that is, it can determine which one or more storage locations the item is stored in.

Step 406: Using a multi-objective genetic algorithm, select a storage box from at least one storage box as the outbound storage box based on the obtained storage location information and multiple preset objectives.

In this embodiment, after obtaining the storage location information of at least one storage box, the server can use a multi-objective genetic algorithm to select one storage box from the at least one storage box. Multiple objectives to be achieved by the algorithm can be preset. After setting the multiple objectives, the storage location information can be used as parameters for the genetic algorithm to calculate the optimal offspring storage box. The multi-objective genetic algorithm can be calculated on a per-order set basis, incorporating all items indicated by the orders included in the order set into the calculation to achieve the preset multiple objectives.

Step 407: Determine the storage location information of the outbound storage box. Based on the preset correspondence between the storage location information and the transportation device, determine the transportation device of the outbound storage box and designate the transportation device of the outbound storage box as the target transportation device.

In this embodiment, the server can determine the storage location information of the outgoing storage box from the acquired storage location information. In a warehouse, a transport device is a device that can transport goods. Each storage box in a storage location is transported by a corresponding transport device. By obtaining the correspondence between storage location information and transport devices, the transport device for the outgoing storage box can be determined using the storage location information of the outgoing storage box. The determined transport device can be designated as the target transport device.

Step 408: Send a transport instruction to the target transport device so that the target transport device transports the outbound storage box to the designated location.

In this embodiment, the server can send a transportation instruction to the determined target transportation device. This instruction instructs the target transportation device to perform transportation, and may include the storage location information of the outgoing storage box and the destination. After receiving the transportation instruction, the target transportation device transports the outgoing storage box to the designated location.

Step 409: Obtain the processing status list of storage boxes to be returned to the warehouse.

In this embodiment, after the transport device moves the outbound storage box to the designated location, it can be further transported to the sorting area by a lift, conveyor, or other transport device to enter the sorting process. After sorting, the storage box can be transported back to the warehouse. The storage location the box is to reach may differ from its previous location and is reset by the server. To reset the storage location, the server needs to obtain the processing status of the storage boxes to be returned from the processing status list. This list records the processing status of the storage boxes to be returned and indicates their status. The processing status of the storage boxes to be returned can include three states: unprocessed, processing, and processed.

Step 410: If there is information on unprocessed storage boxes in the processing status list, then based on multiple specified objectives, a multi-objective genetic algorithm is used to determine the target storage location of the unprocessed storage boxes in the warehouse by using the transportation frequency of the unprocessed storage boxes in the specified historical time period as a parameter.

In this embodiment, if there is information about an unprocessed storage box in the processing status list of storage boxes awaiting return, the server can determine that there are still storage boxes awaiting return. Then, based on multiple specified objectives, the transport frequency of the storage box within a specified historical time period can be used as a parameter to perform a multi-objective genetic algorithm calculation to obtain the target storage location of the storage box in the warehouse.

The calculated objectives for a target storage location can include minimizing the difference in the number of lockers storing items awaiting return across different shelves, and minimizing the time it takes for lockers to be stored. The transport frequency of lockers can indicate the popularity of the items within them; a higher transport frequency indicates higher demand, allowing for the selection of easily accessible storage locations as the target location. For example, a locker storing a particular type of biscuit might be very popular and could be placed on the first shelf. The specified historical time period can be a recent period, such as a month or a week.

In addition to transportation frequency, other parameters can be used for calculation, such as storage location information of storage locations that are currently vacant.

Specifically, the initial storage location can be randomly selected, and then multiple iterations can be performed to obtain the optimal offspring storage location as the target storage location.

Step 411: Send a return instruction to the designated transport device so that the designated transport device transports the unprocessed return-to-warehouse storage box to the target storage location.

In this embodiment, after determining the target storage location, the server can send a return instruction to a designated transport device. This return instruction can include the storage location information of the target location, allowing the designated transport device to transport the storage box to be returned to the target location according to the return instruction. The designated transport device can be one or more types of transport devices, such as elevators, conveyors, and shuttles. Furthermore, the number of designated transport devices can also be one or more.

As can be seen from Figure 4, compared with the embodiment corresponding to Figure 2, the order processing method in this embodiment processes orders according to the server load, ensuring smooth order processing. Furthermore, this embodiment sets the storage location of the returning storage boxes based on the transportation frequency, selecting appropriate storage locations for the returning storage boxes, which is more conducive to shortening the time for the next outbound shipment of the storage boxes.

Referring further to FIG5, as an implementation of the methods shown in the above figures, this application provides an embodiment of an order processing device, which corresponds to the method embodiment shown in FIG2, and the device can be specifically applied to various electronic devices.

As shown in Figure 5, the order processing device 500 of this embodiment includes: an extraction unit 501, an acquisition unit 502, a selection unit 503, a determination unit 504, and a transportation unit 505. The extraction unit 501 is configured to extract item information of items to be shipped from the order to be processed; the acquisition unit 502 is configured to obtain storage location information of at least one storage box storing the items to be shipped in a designated warehouse from a table corresponding to item information and storage location information; the selection unit 503 is configured to use a multi-objective genetic algorithm to select a storage box as the shipping storage box from at least one storage box based on the obtained storage location information and multiple preset objectives; the determination unit 504 is configured to determine the storage location information of the shipping storage box, determine the transportation device of the shipping storage box based on a preset correspondence between storage location information and transportation devices, and designate the transportation device of the shipping storage box as the target transportation device; the transportation unit 505 is configured to send a transportation instruction to the target transportation device so that the target transportation device transports the shipping storage box to a designated location.

In this embodiment, the extraction unit 501 of the order processing device 500 can retrieve orders to be processed from a local database (or memory space) or from a terminal device. The order records the item information of the items to be shipped, and the extraction unit 501 extracts the item information.

In this embodiment, the local database of the acquisition unit 502 can store a correspondence table between item information and storage location information, and this correspondence table is updated in real time. In the warehouse, there can be a large number of storage locations, which are used to store storage boxes containing items. The same item can be placed in one or more storage boxes. The acquisition unit 502 can obtain the storage location information of at least one storage box storing items by searching the aforementioned correspondence table.

In this embodiment, after obtaining the storage location information of at least one storage box, the selection unit 503 can use a multi-objective genetic algorithm to select one storage box from the at least one storage box. Multiple objectives to be achieved by the algorithm can be preset. After setting multiple objectives, the storage location information can be used as parameters of the genetic algorithm to calculate the optimal offspring storage box.

In this embodiment, the determining unit 504 can determine the storage location information of the outgoing storage box from the acquired storage location information. In a warehouse, a transport device is a device that can transport goods. Each storage box in a storage location is transported by a corresponding transport device. By acquiring the correspondence between storage location information and transport devices, the transport device for the outgoing storage box can be determined using the storage location information of the outgoing storage box. The determined transport device can be designated as the target transport device.

In this embodiment, the transportation unit 505 can send a transportation instruction to the determined target transportation device. This instruction instructs the target transportation device to perform transportation, and may include the storage location information of the outgoing storage box and the destination of the transportation. After receiving the transportation instruction, the target transportation device transports the outgoing storage box to the designated location.

In some optional implementations of this embodiment, the order processing device 500 further includes: a list acquisition unit (not shown), configured to acquire a processing status list of storage boxes to be returned to the warehouse, the processing status list of storage boxes to be returned to the warehouse being used to indicate the processing status of storage boxes to be returned to the warehouse; a target determination unit (not shown), configured to, if there is information on storage boxes to be returned to the warehouse that are in an unprocessed state in the processing status list, determine the target storage location of the unprocessed storage boxes to be returned to the warehouse in the warehouse based on multiple specified targets and using a multi-objective genetic algorithm that takes the transportation frequency of the unprocessed storage boxes to be returned to the warehouse within a specified historical time period as a parameter; and a sending unit (not shown), configured to send a return instruction to a specified transportation device so that the specified transportation device transports the unprocessed storage boxes to the target storage location.

In some optional implementations of this embodiment, the order processing device 500 further includes: a status acquisition unit (not shown), configured to acquire an order set processing status list, the order set processing status list being used to indicate the processing status of an order set composed of orders; a quantity determination unit (not shown), configured to determine the quantity of order sets being processed based on the order set processing status list; and a selection unit (not shown), configured to select an order set from at least one order set to be processed in a preset order if the quantity is less than a preset threshold, and to use the orders in the selected order set as orders to be processed.

In some optional implementations of this embodiment, different storage boxes are stored in different storage locations on the shelves, and transport channels for items are set between adjacent shelves on the same floor; and multiple preset objectives include one of the following: minimizing the number of outbound storage boxes, minimizing the difference in the number of storage boxes transported on each transport channel, and minimizing the sum of the times for each outbound storage box to reach the designated location.

Figure 6 shows a schematic diagram of a computer system suitable for implementing the server embodiments of this application. As shown in Figure 6, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage portion 608 into a random access memory (RAM) 603. The RAM 603 also stores various programs and data required for the operation of the system 600. The CPU 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input/output (I/O) interface 605 is also connected to the bus 604.

The following components are connected to I/O interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to I/O interface 605 as needed. A removable medium 611, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 610 as needed so that computer programs read from it can be installed into storage section 608 as needed.

Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 609, and/or installed from removable medium 611. When the computer program is executed by central processing unit (CPU) 601, it performs the functions defined in the methods of this application. It should be noted that the computer-readable medium of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. The computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on a computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and/or flowcharts, and combinations of blocks in the block diagrams and/or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

The units described in the embodiments of this application can be implemented in software or hardware. The described units can also be housed in a processor; for example, a processor can be described as including an extraction unit, an acquisition unit, a selection unit, a determination unit, and a transportation unit. The names of these units do not necessarily limit the specific unit itself; for example, an extraction unit can also be described as "a unit that extracts item information of items to be shipped from an order to be processed."

In another aspect, this application also provides a computer-readable medium, which may be included in the apparatus described in the above embodiments; or it may exist independently and not assembled into the apparatus. The computer-readable medium carries one or more programs, which, when executed by the apparatus, cause the apparatus to: extract item information of items to be shipped from an order to be processed; obtain storage location information of at least one storage box storing the items to be shipped in a designated warehouse from a table of correspondence between item information and storage location information; select a storage box as the shipping storage box from at least one storage box using a multi-objective genetic algorithm based on the obtained storage location information and multiple preset objectives; determine the storage location information of the shipping storage box, determine the shipping device of the shipping storage box based on the preset correspondence between storage location information and transportation devices, and designate the shipping device of the shipping storage box as the target shipping device; and send a transportation instruction to the target shipping device to transport the shipping storage box to a designated location.

The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims (9)

1. An order processing method, characterized in that the method comprises: Extract the item information of items to be shipped from the pending orders; From the correspondence table between item information and storage location information, obtain the storage location information of at least one storage box storing the item to be shipped in the designated warehouse; wherein, the same item to be shipped is stored in multiple storage boxes, different storage boxes are stored in different storage locations on the shelves, and a transport channel for the item is set between adjacent shelves on the same floor. Using a multi-objective genetic algorithm, a storage box is selected as an outgoing storage box from the multiple storage boxes based on the acquired storage location information and multiple preset objectives; the multiple preset objectives include at least one of the following: minimizing the number of outgoing storage boxes, minimizing the difference in the number of storage boxes transported on each transportation channel, and minimizing the sum of the times for each outgoing storage box to reach the designated location. The storage location information of the outbound storage box is determined. Based on the preset correspondence between the storage location information and the transportation device, the transportation device of the outbound storage box is determined, and the transportation device of the outbound storage box is identified as the target transportation device. Send a transport instruction to the target transport device so that the target transport device transports the outbound storage box to the designated location. 2. The order processing method according to claim 1, characterized in that, after sending a transportation instruction to the target transportation device to cause the target transportation device to transport the outbound storage box to the designated location, the method further includes: Obtain the processing status list of storage boxes to be returned to the warehouse. The processing status list of storage boxes to be returned to the warehouse is used to indicate the processing status of the storage boxes to be returned to the warehouse. If the processing status list contains information about unprocessed storage boxes awaiting return, then based on multiple specified objectives, a multi-objective genetic algorithm is used to determine the target storage location of the unprocessed storage boxes awaiting return in the warehouse, using the transportation frequency of the unprocessed storage boxes awaiting return within a specified historical time period as a parameter. Send a return instruction to the designated transport device so that the designated transport device transports the unprocessed return storage box to the target storage location. 3. The order processing method according to claim 1, characterized in that, before retrieving the item information of the items to be shipped recorded in the order to be processed, the method further includes: Obtain the order set processing status list, which is used to indicate the processing status of the order set consisting of orders; Based on the order set processing status list, determine the number of order sets currently being processed; If the quantity is less than a preset threshold, an order set is selected from at least one order set to be processed in a preset order, and the orders in the selected order set are taken as orders to be processed. 4. The order processing method according to claim 1, wherein the transport device is a shuttle car. 5. An order processing device, characterized in that the device comprises: Extraction unit, configured to extract item information of items to be shipped from orders to be processed; The acquisition unit is configured to acquire, from the correspondence table between item information and storage location information, the storage location information of at least one storage box storing the item to be shipped in the designated warehouse; wherein, the same item to be shipped is stored in multiple storage boxes, different storage boxes are stored in different storage locations on the shelves, and a transport channel for the item is set between adjacent shelves on the same floor. The selection unit is configured to use a multi-objective genetic algorithm to select a storage box as an outgoing storage box from the plurality of storage boxes based on the acquired storage location information and a plurality of preset objectives; the plurality of preset objectives include at least one of the following: minimizing the number of outgoing storage boxes, minimizing the difference in the number of storage boxes transported on each transport channel, and minimizing the sum of the times when each outgoing storage box arrives at the designated location. The determining unit is configured to determine the storage location information of the outbound storage box, determine the transportation device of the outbound storage box according to the preset correspondence between the storage location information and the transportation device, and determine the transportation device of the outbound storage box as the target transportation device. The transportation unit is configured to send transportation instructions to the target transportation device so that the target transportation device transports the outbound storage box to a designated location. 6. The order processing apparatus according to claim 5, characterized in that the apparatus further comprises: The list acquisition unit is configured to acquire a list of processing statuses of storage boxes to be returned to the warehouse. The list of processing statuses of storage boxes to be returned to the warehouse is used to indicate the processing status of the storage boxes to be returned to the warehouse. The target unit is configured to determine the target storage location of the unprocessed storage box in the warehouse if there is information on an unprocessed storage box in the processing status list. This is done using a multi-objective genetic algorithm that takes the transportation frequency of the unprocessed storage box in a specified historical time period as a parameter, based on multiple specified targets. The sending unit is configured to send a return instruction to a designated transport device, so that the designated transport device transports the unprocessed storage box to the target storage location. 7. The order processing apparatus according to claim 5, characterized in that the apparatus further comprises: A status acquisition unit is configured to acquire a list of processing statuses for an order set, the list of processing statuses for indicating the processing status of an order set consisting of orders. The quantity determination unit is configured to determine the quantity of the order set being processed based on the order set processing status list; The selection unit is configured to select an order set from at least one order set to be processed in a preset order if the quantity is less than a preset threshold, and to take the orders in the selected order set as orders to be processed. 8. A server, comprising: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-4. 9. A computer-readable storage medium having a computer program stored thereon, characterized in that the program, when executed by a processor, implements the method as described in any one of claims 1-4.