WO2022206308A1 - 订单分配方法、装置、设备及存储介质 - Google Patents

订单分配方法、装置、设备及存储介质 Download PDF

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Publication number
WO2022206308A1
WO2022206308A1 PCT/CN2022/079744 CN2022079744W WO2022206308A1 WO 2022206308 A1 WO2022206308 A1 WO 2022206308A1 CN 2022079744 W CN2022079744 W CN 2022079744W WO 2022206308 A1 WO2022206308 A1 WO 2022206308A1
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WIPO (PCT)
Prior art keywords
picking
workstation
orders
virtual slots
efficiency
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PCT/CN2022/079744
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English (en)
French (fr)
Inventor
周红霞
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深圳市库宝软件有限公司
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Publication of WO2022206308A1 publication Critical patent/WO2022206308A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311—Scheduling, planning or task assignment for a person or group

Definitions

  • the present application relates to the technical field of intelligent warehousing, and in particular, to an order distribution method, device, equipment and storage medium.
  • a put wall is a rack that includes a plurality of slots, wherein each slot corresponds to one or more orders for placing goods corresponding to the order.
  • the warehouse management system uses batch picking and order merging methods to aggregate orders from multiple orders to re-form multiple target orders. After that, the picking system picks the goods required for each target order from the warehouse, and then sows the goods required for the target order into the slots corresponding to the placement wall.
  • the number of slots is related to the number of orders it can handle, i.e. with a few slots in the put wall, the picking station can only take a fixed number of orders. In this way, the number of order tasks that the picking station needs to process is fixed.
  • the present application provides an order distribution method, device, device and storage medium, which are used to solve the problem that the amount of order tasks processed by a picking workstation is fixed.
  • an embodiment of the present application provides an order allocation method, including: acquiring a plurality of orders to be processed; acquiring the number of virtual slots of each picking workstation; wherein the number of virtual slots of each picking workstation is based on a predetermined number of The configuration rule is configured to indicate the number of pending orders that can be processed by the picking workstation; according to the number of virtual slots of each picking workstation, the multiple pending orders are allocated to each picking workstation.
  • the number of virtual slots of each picking station is the same or different.
  • the method further includes: configuring the number of virtual slots for each picking station according to a preset configuration rule.
  • the preset configuration rules include: according to the picking efficiency of each picking workstation, or the repetition rate of the same stock keeping unit in multiple orders to be processed, or the offline time of the picking personnel, or The number of picking robots, and the number of virtual slots configured for each picking station.
  • the preset configuration rule includes: configuring the number of virtual slots for each picking workstation according to at least two of the following configuration parameters: picking efficiency of each picking workstation; The repetition rate of the same stock keeping unit; the offline time of picking personnel; the number of picking robots; among them, each configuration parameter corresponds to a configuration result; the average of at least two configuration results of each picking station, or the The maximum of at least two configuration results is taken as the number of virtual slots of the picking station.
  • configuring the number of virtual slots for each picking workstation according to a preset configuration rule includes: obtaining the picking efficiency of each picking workstation in the storage system; according to the picking efficiency of each picking workstation , configure the number of virtual slots for each picking workstation; wherein, the number of virtual slots configured for each picking workstation is positively related to the picking efficiency of the picking workstation.
  • configuring the number of virtual slots for each picking workstation according to the picking efficiency of each picking workstation includes: if the picking efficiency of each picking workstation is the same, configuring the same number for each picking workstation virtual slot.
  • configuring the number of virtual slots for each picking workstation according to the picking efficiency of each picking workstation includes: if the picking efficiency of each picking workstation is different, determining the sum of the picking efficiency of each picking workstation , obtain the total picking efficiency; determine the ratio of the picking efficiency of each picking workstation to the total picking efficiency; according to the ratio of the picking efficiency of each picking workstation to the total picking efficiency, and the number of the multiple orders to be processed , the number of virtual slots configured for each picking workstation; wherein, the number of virtual slots configured for each picking workstation is the ratio of the picking efficiency of the picking workstation to the total picking efficiency, and the total number of orders
  • the product of the total order includes the plurality of pending orders and the assigned orders of all picking stations.
  • configuring the number of virtual slots for each picking workstation according to the picking efficiency of each picking workstation includes: if the picking efficiency of each picking workstation is different, and the picking efficiency of the current picking workstation is lower than a predetermined value; If the picking efficiency threshold is set, the current picking workstation is configured with a first number of virtual slots; if the picking efficiency of each picking workstation is different, and the picking efficiency of the current picking workstation is higher than or equal to the preset picking efficiency threshold, then A second number of virtual slots is configured for the current picking station; wherein the second number is greater than the first number.
  • the configuring the number of virtual slots for each picking workstation according to a preset configuration rule includes: determining, among the multiple pending orders, a pending order having the same stock keeping unit The number of processed orders; the number of virtual slots is configured for each picking workstation according to the number of pending orders with the same stock keeping unit in the plurality of pending orders, and the number of orders allocated to each picking workstation.
  • configuring the number of virtual slots for each picking workstation according to the number of pending orders with the same stock keeping unit and the number of orders allocated to each picking workstation according to the plurality of pending orders including: Determining the repetition rate of the stock keeping units in the multiple pending orders; determining the sum of the number of pending orders corresponding to the stock keeping unit with the largest repetition rate and the number of orders allocated by each picking workstation as the individual picking.
  • the number of virtual slots of the workstation wherein the number of virtual slots configured for each picking workstation is the number of pending orders with the same stock keeping unit among the plurality of pending orders, which is the same as the number of allocated virtual slots of the picking workstation The sum of the order quantities.
  • the number of pending orders with the same stock keeping unit and the number of orders allocated to each picking workstation for each picking The workstation configures the number of virtual slots, including: from the multiple pending orders, allocating an order to the picking workstation as a target order; determining the remaining pending orders in the multiple pending orders, and the The repetition rate of the inventory holding unit in the target order; the sum of the number of pending orders corresponding to the inventory holding unit with the maximum repetition rate and the number of orders allocated by the current picking workstation is determined as the virtual slot of the picking workstation quantity.
  • the configuring the number of virtual slots for each picking workstation according to a preset configuration rule includes: determining according to the total number of picking robots and the number of picking workstations The number of picking robots corresponding to each picking workstation; wherein the number of virtual slots of each picking workstation is less than or equal to the number of picking robots corresponding to the picking workstation, and the picking robots are used to transport the picked goods to the next operation The destination of the process.
  • the configuring the number of virtual slots for each picking station according to a preset configuration rule includes: determining a time difference between a current time and a preset time, the preset time Determined according to the offline time of the picking staff at the workstation; according to the time difference and the work efficiency of the picking staff, configure a third number of virtual slots for the workstation corresponding to the picking staff; the work efficiency of the picking staff is The quantity of goods that can be picked by the picking staff in a unit time; wherein, the third quantity is the quantity of goods that the picking staff can pick within the time difference range corresponding to the quantity of orders to be processed.
  • configuring a third number of virtual slots for the workstation corresponding to the picking staff includes: multiplying the time difference and the work efficiency of the picking staff, The number of corresponding pending orders is determined as the number of virtual slots configured for the workstations corresponding to the picking personnel.
  • an embodiment of the present application provides an order distribution device, including: an acquisition module, configured to acquire multiple orders to be processed; the acquisition module is further configured to acquire the number of virtual slots of each picking workstation; wherein, The number of virtual slots of each picking station is configured according to preset configuration rules, and is used to indicate the number of pending orders that can be processed by the picking station; the allocation module is used to allocate virtual slots according to the configuration of each picking station. quantity, the plurality of pending orders are distributed to the respective picking stations.
  • the number of virtual slots of each picking station is the same or different.
  • it further includes: a configuration module, configured to configure the number of virtual slots for each picking station according to a preset configuration rule.
  • the preset configuration rules include: according to the picking efficiency of each picking workstation, or the repetition rate of the same stock keeping unit in multiple orders to be processed, or the offline time of the picking personnel, or The number of picking robots, and the number of virtual slots configured for each picking station.
  • the preset configuration rule includes: configuring the number of virtual slots for each picking workstation according to at least two of the following configuration parameters: picking efficiency of each picking workstation; The repetition rate of the same stock keeping unit; the offline time of picking personnel; the number of picking robots; among them, each configuration parameter corresponds to a configuration result; the average of at least two configuration results of each picking station, or the The maximum of at least two configuration results is taken as the number of virtual slots of the picking station.
  • the configuration module is specifically used to: obtain the picking efficiency of each picking workstation in the storage system; configure virtual slots for each picking workstation according to the picking efficiency of each picking workstation Among them, the number of virtual slots configured in each picking station is positively related to the picking efficiency of the picking station.
  • the configuration module is specifically used for: if the picking efficiency of each picking station is the same, configure the same number of virtual slots for each picking station.
  • configure the module which is specifically used to: if the picking efficiency of each picking workstation is different, determine the sum of the picking efficiency of each picking workstation to obtain the total picking efficiency; determine the difference between the picking efficiency of each picking workstation and the total picking efficiency. Ratio; according to the ratio of the picking efficiency of each picking workstation to the total picking efficiency, and the number of the total order, configure the number of virtual slots for each picking workstation, and the total order includes the multiple The order to be processed and the assigned orders of all picking stations; wherein, the number of virtual slots configured for each picking station is the ratio of the picking efficiency of the picking station to the total picking efficiency, and the product of the total number of orders .
  • the configuration module is specifically used for: if the picking efficiency of each picking workstation is different, and the picking efficiency of the current picking workstation is lower than the preset picking efficiency threshold, configure the current picking workstation with a first number of virtual slots If the picking efficiency of each picking workstation is different, and the picking efficiency of the current picking workstation is higher than or equal to the preset picking efficiency threshold, a second number of virtual slots is configured for the current picking workstation; The second number is greater than the first number.
  • the configuration module is specifically configured to: determine the number of pending orders with the same stock keeping unit among the multiple pending orders; , the number of pending orders with the same stock-holding unit, the number of allocated orders for each picking station, and the number of virtual slots configured for each picking station.
  • the configuration module is used to determine the repetition rate of the stock keeping units in the plurality of pending orders; the quantity of the pending orders corresponding to the stock keeping unit with the maximum repetition rate and the quantity of the orders allocated by each picking station are calculated and, determine the number of virtual slots for each picking workstation, wherein the number of virtual slots configured for each picking workstation is the number of pending orders with the same stock keeping unit in the plurality of pending orders , plus the number of allocated orders for this picking station.
  • the configuration module is specifically configured to: from the plurality of orders to be processed, assign an order to the picking workstation as a target order; determine the plurality of orders to be processed The repetition rate of the remaining pending orders in the processing order and the stock keeping unit in the target order; the sum of the number of pending orders corresponding to the stock keeping unit with the largest repetition rate and the number of orders allocated by the current picking workstation, Determine the number of virtual slots for the picking station.
  • the configuration module is specifically configured to: determine the number of picking robots corresponding to each picking workstation according to the total number of picking robots and the number of picking workstations; wherein, The number of virtual slots in each picking workstation is less than or equal to the number of picking robots corresponding to the picking workstation, and the picking robots are used to transport the picked goods to the destination of the next operation process.
  • the configuration module is specifically configured to: determine a time difference between a current time and a preset time, where the preset time is determined according to the offline time of the picker of the workstation; According to the time difference and the work efficiency of the picker, a third number of virtual slots are configured for the workstation corresponding to the picker; the work efficiency of the picker is the number of goods that the picker can pick in a unit time; Wherein, the third quantity is the quantity of the goods that the picking personnel can pick within the time difference range corresponding to the quantity of the orders to be processed.
  • the configuration module is configured to determine the product of the time difference and the work efficiency of the picking personnel, and the corresponding number of orders to be processed, as the number of virtual slots configured for the workstations corresponding to the picking personnel.
  • the present application provides a computer device, including: a processor, a memory, and a transceiver;
  • the memory stores computer-executable instructions
  • the processor implements the first aspect and the order allocation method provided by each possible design when executing the computer program instructions.
  • the present application provides a computer-readable storage medium, where computer program instructions are stored in the computer-readable storage medium, and when the computer program instructions are executed by a processor, are used to implement the first aspect and various possible designs Provided order allocation method.
  • embodiments of the present application provide a computer program product, including a computer program, which is used to implement the first aspect and the order allocation method provided by each possible design when the computer program is executed by a processor.
  • Embodiments of the present application provide an order allocation method, device, device, and storage medium.
  • the number of virtual slots of each picking workstation is acquired by acquiring multiple orders to be processed;
  • the number of virtual slots is configured according to preset configuration rules to indicate the number of pending orders that the picking station can handle; according to the number of virtual slots of each picking station, multiple pending orders are allocated to each picking station workstation.
  • the number of virtual slots of each picking workstation is dynamically configured, which solves the order task processed by the picking workstation Amount is a fixed issue.
  • FIG. 1A is a schematic diagram of an intelligent warehouse provided by an embodiment of the present application.
  • FIG. 1B is a schematic diagram of intelligent warehousing in the related art
  • FIG. 2 is a flowchart of Embodiment 1 of an order allocation method provided by an embodiment of the present application
  • Embodiment 2 is a flowchart of Embodiment 2 of the order allocation method provided by the embodiment of the present application;
  • FIG. 4 is a flowchart of Embodiment 3 of the order allocation method provided by the embodiment of the present application.
  • FIG. 4A is an example diagram of an implementation manner provided by an embodiment of the present application.
  • FIG. 4B is an example diagram of another implementation manner provided by the embodiment of the present application.
  • FIG. 5 is a flowchart of Embodiment 4 of the order allocation method provided by the embodiment of the present application.
  • FIG. 6 is a schematic structural diagram of an order distribution device provided by an embodiment of the present application.
  • FIG. 7 is a schematic structural diagram of a computer device provided by an embodiment of the present application.
  • FIG. 1A is a schematic diagram of a smart warehouse provided by an embodiment of the present application. As shown in FIG. 1A, it includes a control device 11, a warehouse 12, a handling robot 13, a picking workstation 14, a picking robot 15 and a packing station 16; wherein, the control device 11 can be a server, a terminal, etc., and the control device 11 can be installed with Warehouse management system.
  • the control device 11 receives the order.
  • the warehouse management system installed on the control device 11 merges the commodities contained in the orders received in each batch to form waves, and determines the bins in the warehouse 12 that contain the commodities in the orders, and then transports the bins by the handling robot 13
  • the sorted goods are transported to the sorting compartment 16 by the sorting robot 15, and then packed out of the warehouse.
  • FIG. 1B it includes a control device 21 , a warehouse 22 , a handling robot 23 , a picking workstation 24 , a picking person 251 , a picking person 252 and a placement wall 26 ; each workstation corresponds to one or more placement walls 26 , after the transport robot 23 transports the goods or bins to the picking workstation 24 , the sorting of the goods is completed through the placement wall 26 . That is, the picking personnel 251 scan the barcodes of the bins transported to the workstation one by one with a barcode gun, and play the picked goods to the lit notch according to the lighting instructions of the slot on the planting wall.
  • the picker 252 on the back of the put wall can carry out secondary sorting or review and packing of the orders in the light slot.
  • the slot of the put wall is a solid slot, and the number is fixed, so a station can receive a fixed number of orders at most. Therefore, the handling robot may carry the same material box back and forth multiple times, resulting in low picking efficiency.
  • the maximum order quantity that the planting wall can receive is 10. If WMS receives 20 orders, all 20 orders require toothpaste, then the handling robot will move the toothpaste container from the warehouse to the planting wall. After 10 orders are completed, the container needs to be transported back to the warehouse. After that, the WMS system If another 10 orders are issued to the planting wall, the handling robot needs to move the toothpaste material box again. In this way, the same material box needs to be handled multiple times, which increases the time cost and leads to low picking efficiency.
  • the technical conception process of the inventor is as follows: using virtual notches to replace the physical notches of the seeding wall, and configuring the number of virtual notches according to the working capacity of each workstation, that is, the maximum number of orders that can be received In this way, the work capacity of each workstation will change dynamically, so the number of virtual slots can be dynamically configured, so that the number of orders that each workstation can receive can be flexibly allocated.
  • FIG. 2 is a flowchart of Embodiment 1 of the order allocation method provided by the embodiment of the present application. As shown in Figure 2, the order allocation method may include the following steps:
  • Step S201 acquiring multiple pending orders.
  • the multiple pending orders may be orders sent by the user equipment received by the warehouse management system within a period of time.
  • the warehouse management system receives orders sent by user equipment every day.
  • Step S202 Acquire the number of virtual slots of each picking workstation; wherein, the number of virtual slots of each picking workstation is configured according to a preset configuration rule to indicate the number of pending orders that can be processed by the picking workstation.
  • the number of virtual slots of each picking station is dynamically configured according to preset configuration rules.
  • the number of virtual slots can be based on each picking station
  • the number of orders that the workstation can handle is determined.
  • the number of virtual slots configured by the picking workstation is the number of orders that the picking workstation can process at one time.
  • the number of virtual slots of each picking station may be pre-configured according to a preset configuration rule, and stored in the control device. Therefore, when order allocation needs to be performed, the number of virtual slots configured for each picking station is directly obtained, and order allocation is performed.
  • the number of virtual slots of each picking station may be configured in real time. That is, after multiple pending orders are acquired, the number of virtual slots of each picking station may be configured according to a preset configuration rule. It is also possible to configure the number of virtual slots of each picking station according to a preset configuration rule before acquiring multiple pending orders. It may also be that each time period is updated according to a preset configuration rule, etc., which is not limited here.
  • the configuration process of the number of virtual slots of each workstation can be performed one or more times; if performed once, the configured number of virtual slots is used for each order allocation process. If executed multiple times, the current number of virtual slots is matched for each order allocation process.
  • Step S203 according to the number of virtual slots of each picking workstation, allocating multiple orders to be processed to each picking workstation.
  • a pending order corresponds to a virtual slot.
  • multiple orders in the multiple pending orders belong to the single item and single item type, that is, a pending order includes a sub-order, and the sub-order includes one commodity.
  • this type of of pending orders are assigned to the same virtual slot.
  • the virtual slot can be implemented by a picking robot, which means that the function of storing goods in the physical slot can be implemented by the picking robot.
  • the picking robot can be an AGV (Automated Guided Vehicle) trolley, a jacking robot, and a tipping robot.
  • the picking robot transports the material box to the picking workstation
  • the staff places the goods corresponding to the orders allocated by the picking workstation on the pallet of the picking robot
  • the picking robot transports the goods to the destination of the next operation process, such as , and transport it to the destination of packaging and delivery for packaging and delivery.
  • it returns to the picking workstation receives other goods corresponding to the orders allocated by the picking workstation, and transports them to the destination of the next operation process. By repeating this for many times, the goods corresponding to the orders allocated by the picking station can be completed.
  • each picking workstation corresponds to at least one picking robot, and the at least one picking robot receives at least one item of the order assigned to the picking workstation each time.
  • this embodiment can configure 20 virtual slots for the picking workstation at one time. , then after the handling robot transports the toothpaste container to the picking workstation, the picking workstation can complete the selection of toothpaste requirements in 20 orders at one time, and the handling robot only needs to carry the toothpaste container once, no need to go back and forth. Therefore, the hit rate of one tote for multiple pending orders can be improved, thereby reducing the handling time and improving the picking efficiency.
  • the order allocation method of this embodiment by acquiring multiple orders to be processed, and acquiring the number of virtual slots of each picking workstation; wherein, the number of virtual slots of each picking workstation is configured according to a preset configuration rule, using It is used to indicate the number of pending orders that the picking workstation can handle; and according to the number of virtual slots of each picking workstation, multiple pending orders are allocated to each picking workstation.
  • the number of virtual slots of each picking station is configured according to a preset configuration rule, the number of virtual slots of each picking station is dynamically configured, which solves the order task of placing the wall. The quantity is fixed, which leads to the problem of inefficient picking.
  • the number of virtual slots of each picking station can be the same or different.
  • the preset configuration rules may include configuring the same or different numbers of virtual slots for each picking station.
  • the number of virtual slots of each picking station determines how many pending orders the picking station can receive.
  • the number of pending orders that the picking workstation can receive will affect the number of pending orders that are hit by the same bin. Then, if the number of pending orders that can be received by a single workstation is greater, the number of pending orders that can be hit by the same bin will also be greater. In turn, the number of times the handling robot handles the bins will be reduced, thereby improving the picking efficiency.
  • the number of virtual slots configuring each picking station is critical.
  • the order distribution method of this embodiment further includes the following steps: configure the number of virtual slots for each picking workstation according to a preset configuration rule.
  • the preset configuration rules include: configuring virtual slots for each picking workstation according to the picking efficiency of each picking workstation, the repetition rate of the same stock keeping unit in multiple pending orders, the offline time of picking personnel or the number of robots number of mouths.
  • the number of virtual slots can be configured for each picking workstation according to the picking efficiency of each picking workstation, or the virtual slots can be configured for each picking workstation according to the repetition rate of the same stock keeping unit in multiple orders to be processed.
  • the number of slots, the number of virtual slots can also be configured for each picking station according to the offline time of the picking personnel, and the number of virtual slots can also be configured for each picking station according to the number of robots.
  • the preset configuration rule may further include: configuring the number of virtual slots for each picking station according to at least two of the following configuration parameters:
  • each of the above configuration parameters corresponds to a configuration result
  • Each picking station can obtain four configuration results, and the average of the four configuration results is used as the number of virtual slots of the picking station.
  • each picking station with a virtual slot based on each of its picking efficiency, the repetition rate of the same stock-holding unit in multiple pending orders, the offline time of the picker, and the number of robots. Quantities are detailed:
  • FIG. 3 is a flowchart of Embodiment 2 of the order allocation method provided by the embodiment of the present application.
  • the order allocation method provided by the embodiment of the present application will be described in detail below with reference to FIG. 3 . As shown in Figure 3, it includes the following steps:
  • Step S301 acquiring the picking efficiency of each picking workstation in the storage system.
  • the picking efficiency of a picking workstation is the quantity of goods that can be picked by the picking workstation in a unit time.
  • the picking efficiency of each picking workstation can be determined in advance and stored in the control device.
  • determining the picking efficiency of each picking workstation includes: obtaining the number of goods picked by each workstation per day; calculating the number of goods picked by each picking workstation per unit time according to the number of goods picked by each workstation per day, and obtaining the picking efficiency of each picking workstation . It should be noted that for each picking workstation, the same picking workstation has different picking personnel, and the picking efficiency is different; or, for different picking workstations, if some picking workstations use manual picking, and some picking workstations use mechanical picking, then manual picking. And the efficiency of mechanical picking is also different.
  • the picking efficiency of the picking workstation N/24, and the unit is: pieces/hour.
  • Step S302 configure the number of virtual slots for each picking workstation according to the picking efficiency of each picking workstation.
  • the number of virtual slots configured in each picking station is positively related to the picking efficiency of the picking station.
  • the positive correlation can be understood as the higher the picking efficiency of the picking station, the more the number of virtual slots of the picking station; conversely, the lower the picking efficiency of the picking station, the less the number of virtual slots of the picking station.
  • step S302 can be realized by at least one of the following implementation manners:
  • step S302 may include the following steps: if the picking efficiency of each picking workstation is the same, configure the same number of virtual slots for each picking workstation; if the picking efficiency of each picking workstation is different, A different number of virtual slots is then configured for each picking station.
  • step S302 may include the following steps:
  • Step a1 If the picking efficiency of each picking workstation is different, determine the sum of the picking efficiency of each picking workstation to obtain the total picking efficiency.
  • Step a2 Determine the ratio of the picking efficiency of each picking workstation to the total picking efficiency.
  • Step a3 According to the ratio of the picking efficiency of each picking workstation to the total picking efficiency and the number of total orders, configure the number of virtual slots for each picking workstation, and the total order includes multiple pending orders and all the allocated orders of the picking workstations .
  • the number of virtual slots configured in each picking workstation is the ratio of the picking efficiency of the picking workstation to the total picking efficiency, and the product of the total number of orders.
  • the number of virtual slots of each picking station can be expressed as the following formula:
  • e i is the picking efficiency of the picking workstation numbered i
  • M is the total number of picking workstations
  • D is the number of total orders
  • a i is the number of virtual slots of the picking workstation numbered i.
  • step S302 may include the following steps:
  • Step b1 If the picking efficiency of each picking workstation is different, and the picking efficiency of the current picking workstation is lower than the preset picking efficiency threshold, configure a first number of virtual slots for the current picking workstation.
  • Step b2 If the picking efficiency of each picking workstation is different, and the picking efficiency of the current picking workstation is higher than or equal to the preset picking efficiency threshold, configure a second number of virtual slots for the current picking workstation; first quantity.
  • a preset picking efficiency threshold can be set, and each picking workstation can be divided into workstations with high picking efficiency and workstations with low picking efficiency, so that the workstation with high picking efficiency has a larger number of virtual slots, and the picking efficiency is low.
  • Inefficient workstations are configured with a lower number of virtual slots. Thus, the picking efficiency of each workstation can be balanced on the whole.
  • the preset picking efficiency threshold may be determined according to the average picking efficiency of each workstation. It should be understood that the determination of the preset picking efficiency threshold based on the average picking efficiency of each workstation is an exemplary illustration, and is not intended to limit the present application. Those skilled in the art can set preset picking efficiency thresholds according to actual needs. For example, take the average of the highest picking efficiency and the lowest picking efficiency.
  • FIG. 4 is a flowchart of Embodiment 3 of the order allocation method provided by the embodiment of the present application.
  • the order allocation method provided by the embodiment of the present application will be described in detail below with reference to FIG. 4 . As shown in Figure 4, it includes the following steps:
  • Step S401 Determine the number of pending orders with the same inventory holding unit among the multiple pending orders.
  • the stock keeping unit is the smallest inventory unit that is physically inseparable, and can be in units of pieces, boxes, pallets, etc.
  • the same style of clothing has two attributes of color and size, then one color and one size can correspond to one SKU.
  • the black S size can be one SKU, and the black M size is one SKU.
  • Step S402 Configure the number of virtual slots for each picking workstation according to the number of pending orders with the same inventory holding unit among the multiple pending orders, and the number of orders allocated to each picking workstation.
  • step S402 includes at least the following two implementations:
  • the number of virtual slots is configured for each picking workstation according to the number of pending orders with the same stock keeping unit among the multiple pending orders, and the number of orders allocated to each picking workstation ,include:
  • Step c1 determining the repetition rate of the stock keeping units in the multiple pending orders.
  • the repetition rate can be defined according to the following method: the number of multiple pending orders is M, and among the M pending orders, the number of pending orders with the same stock keeping unit is m, then the stock keeping unit is repeated Rate: m/M.
  • Step c2 determine the sum of the number of pending orders corresponding to the stock keeping unit with the maximum repetition rate and the number of orders allocated to each picking workstation as the number of virtual slots of each picking workstation, where each picking workstation is configured with The number of virtual slots is the sum of the number of pending orders with the same stock-holding unit among multiple pending orders and the number of allocated orders for this picking station.
  • the number of virtual slots of each picking workstation can be set as the sum of the number of pending orders corresponding to the stock keeping unit with the maximum repetition rate and the number of orders allocated to each picking workstation.
  • each picking workstation includes picking workstation 1, picking workstation 2 and picking workstation 3; the number of allocated orders of picking workstation 1, picking workstation 2 and picking workstation 3 are 10, 20 and 30 respectively;
  • the number of pending orders corresponding to the stock keeping unit with the maximum repetition rate is 30, then the number of virtual slots of Picking Station 1 is 40, the number of virtual slots of Picking Station 2 is 50, and the number of virtual slots of Picking Station 3 is 50.
  • the number of virtual slots is 60.
  • a total of n types of SKUs are included in the multiple orders to be processed.
  • the repetition rate of each SKU needs to be determined, and then the number of orders allocated to each picking station is equal to the maximum repetition rate in SKU1 to SKUn.
  • the sum of the number of pending orders corresponding to the rate is determined as the number of virtual slots of the corresponding picking station.
  • pending orders include A style black S size clothes
  • the repetition rate of A style black S size clothes is 30 %
  • 10 of the pending orders include A style black M size clothes, then the repetition rate of A style black S size clothes is 10%.
  • this embodiment is based on the number of pending orders corresponding to SKUs with a repetition rate of 30%, and the number of orders allocated to the current picking workstation is 10.
  • the number of virtual slots are all set to 40.
  • the virtual slot is configured for each picking station. quantity, including:
  • Step d1 from a plurality of pending orders, assign an order to the picking station as a target order.
  • Step d2 determining the repetition rate of the remaining pending orders among the multiple pending orders and the inventory holding units in the target order.
  • Step d3 Determine the sum of the number of pending orders corresponding to the stock keeping unit with the maximum repetition rate and the number of orders allocated to each picking workstation as the number of virtual slots of the picking workstation.
  • the repetition rate of SKU1 is 40%, and SKU2 is included in 9 orders, and the repetition rate of SKU2 is 10%.
  • the repetition rate of SKU3 is 50%, then the number of pending orders corresponding to SKU3 49 is added to the target order, and the number of orders allocated by the current picking workstation 10 is added as the virtual slot configured for picking workstation 1 The number of mouths is 60.
  • configuring the number of virtual slots according to the repetition rate of SKUs can ensure that when pending orders of the same SKU are allocated to the same picking workstation, the picking workstation can receive these pending orders with the same SKU, and the picking robot When handling the bins, the walking paths can be reduced, thereby reducing the handling time and further improving the picking efficiency.
  • the order distribution method of the embodiment of the present application may further include the following steps: according to the total number of picking robots and the number of picking workstations, determine the number of picking robots corresponding to each picking workstation; The number of virtual slots of a picking workstation is less than or equal to the number of picking robots corresponding to the picking workstation, and the robots are used to transport the picked goods to the destination of the next operation process.
  • the total number of picking robots and the number of picking workstations may be further used to determine the number of picking robots corresponding to each picking workstation quantity.
  • the number of picking robots corresponding to each picking workstation may also be determined independently according to the total number of picking robots and the number of picking workstations. The sum of the number of picking robots corresponding to each picking workstation is less than or equal to the total number of picking robots.
  • the number of virtual slots of each picking workstation is less than or equal to the number of picking robots corresponding to the picking workstation, which can avoid that the number of picking robots in one picking workstation is too small and the number of virtual slots is too large, which may lead to picking robots.
  • the picking goods cannot be received at the first time, resulting in the accumulation of the picking goods at the workstation.
  • FIG. 5 is a flowchart of Embodiment 4 of the order allocation method provided by the embodiment of the present application.
  • the order allocation method provided by the embodiment of the present application will be described in detail below with reference to FIG. 5 . As shown in Figure 5, it includes the following steps:
  • Step S501 Determine the time difference between the current time and the preset time, and the preset time is determined according to the offline time of the picking personnel of the workstation.
  • Step S502 according to the time difference and the work efficiency of the pickers, configure a third number of virtual slots for the picking workstations corresponding to the pickers; the work efficiency of the pickers is the number of goods that the pickers can pick per unit time.
  • the third quantity is the quantity of pending orders corresponding to the goods that the picking personnel can pick within the time difference range.
  • a third number of virtual slots are configured for the picking workstations corresponding to the pickers, including: multiplying the time difference and the work efficiency of the pickers, and the corresponding number of pending orders, determine The number of virtual slots configured for workstations corresponding to pickers.
  • the picking workstation corresponding to the picker is configured with 40 Virtual slot.
  • the number of virtual slots is configured for the picking workstation corresponding to the picker, so that the number of virtual slots can be flexibly configured to ensure work efficiency.
  • Staff are off the line on time.
  • the method of this embodiment may further include the following steps:
  • Step f1 Receive a picking completion signal sent by the scanning terminal after scanning the goods in the order to be processed.
  • Step f2 according to the signal of picking completion, update the status information of the goods in the order to be processed.
  • Step f3 after receiving the signal that the picking of all goods in the order to be processed is completed, send the signal of picking completion to the terminal corresponding to the next operation process.
  • the handling robot transports the bin corresponding to the goods required by the workstation to the workstation area, and the picker of the workstation scans the cargo in the bin with the scanning terminal, and then the scanning terminal will send a signal of picking completion.
  • the control device changes the status information of the goods in the WMS system to picking completed, to be packaged out of the warehouse; the control device determines the pending order according to the goods corresponding to the pending orders assigned to the workstation and the goods that have been picked. Whether the corresponding goods have been picked, so as to ensure the accuracy of the quantity of goods corresponding to the virtual slot.
  • FIG. 6 is a schematic structural diagram of an order distribution apparatus provided by an embodiment of the present application.
  • the order distribution device includes: an acquisition module 61 and an allocation module 62 .
  • the acquisition module 61 is used to acquire multiple pending orders; the acquisition module 61 is also used to acquire the number of virtual slots of each picking workstation; wherein, the number of virtual slots of each picking workstation is configured according to a preset
  • the rules are configured to indicate the number of pending orders that can be processed by the picking workstation; the allocation module 62 is used to distribute the multiple pending orders to each picking workstation according to the number of virtual slots of each picking workstation.
  • the number of virtual slots of each picking station is the same or different.
  • the configuration module 63 is further included, configured to configure the number of virtual slots for each picking station according to a preset configuration rule.
  • the preset configuration rules include: according to the picking efficiency of each picking workstation, or the repetition rate of the same stock keeping unit in multiple orders to be processed, or the offline time of the picking personnel, or The number of picking robots, and the number of virtual slots configured for each picking station.
  • the preset configuration rule includes: configuring the number of virtual slots for each picking workstation according to at least two of the following configuration parameters: picking efficiency of each picking workstation; The repetition rate of the same stock keeping unit; the offline time of picking personnel; the number of picking robots; among them, each configuration parameter corresponds to a configuration result; the average of at least two configuration results of each picking station, or the The maximum of at least two configuration results is taken as the number of virtual slots of the picking station.
  • the configuration module 63 is specifically used to: obtain the picking efficiency of each picking workstation in the storage system; configure virtual slots for each picking workstation according to the picking efficiency of each picking workstation The number of slots; among them, the number of virtual slots configured in each picking station is positively related to the picking efficiency of the picking station.
  • the configuration module 63 is specifically configured to configure the same number of virtual slots for each picking workstation if the picking efficiency of each picking workstation is the same.
  • the configuration module 63 is specifically configured to: if the picking efficiency of each picking workstation is different, determine the sum of the picking efficiency of each picking workstation to obtain the total picking efficiency; determine the picking efficiency of each picking workstation and the total picking efficiency According to the ratio of the picking efficiency of each picking workstation to the total picking efficiency, and the number of the total order, configure the number of virtual slots for each picking workstation, and the total order includes the multiple A number of pending orders and assigned orders of all picking workstations; wherein, the number of virtual slots configured for each picking workstation is the ratio of the picking efficiency of the picking workstation to the total picking efficiency, and the total number of orders product.
  • the configuration module 63 is specifically configured to: if the picking efficiency of each picking workstation is different, and the picking efficiency of the current picking workstation is lower than the preset picking efficiency threshold, configure the current picking workstation with a first number of virtual Slots; if the picking efficiency of each picking workstation is different, and the picking efficiency of the current picking workstation is higher than or equal to the preset picking efficiency threshold, a second number of virtual slots is configured for the current picking workstation; wherein, the The second number is greater than the first number.
  • the configuration module 63 is specifically configured to: determine the number of pending orders with the same stock keeping unit among the multiple pending orders; In the order, the number of pending orders with the same stock-holding unit, the number of orders allocated to each picking station, and the number of virtual slots configured for each picking station.
  • the configuration module 63 is configured to determine the repetition rate of the stock keeping units in the plurality of pending orders; the quantity of the pending orders corresponding to the stock keeping unit with the largest repetition rate is compared with the quantity of the assigned orders of each picking workstation The sum is determined as the number of virtual slots of each picking workstation, wherein the number of virtual slots configured by each picking workstation is the number of pending orders with the same stock keeping unit in the multiple pending orders. Quantity, plus the quantity of the assigned order for this picking station.
  • the configuration module 63 is specifically configured to: from the multiple orders to be processed, assign an order to the picking workstation as a target order; determine the multiple orders The repetition rate of the remaining pending orders in the pending orders and the stock-keeping unit in the target order; the sum of the number of pending orders corresponding to the stock-keeping unit with the largest repetition rate and the number of orders allocated by the current picking workstation , determines the number of virtual slots for the picking station.
  • the configuration module 63 is specifically configured to: determine the number of picking robots corresponding to each picking workstation according to the total number of picking robots and the number of picking workstations; wherein , the number of virtual slots of each picking workstation is less than or equal to the number of picking robots corresponding to the picking workstation, and the picking robots are used to transport the picked goods to the destination of the next operation process.
  • the configuration module 63 is specifically configured to: determine a time difference between the current time and a preset time, where the preset time is determined according to the offline time of the picking personnel of the workstation ; According to the time difference and the work efficiency of the pickers, configure a third number of virtual slots for the workstations corresponding to the pickers; the work efficiency of the pickers is the number of goods that the pickers can pick per unit time ; wherein, the third quantity is the quantity of the goods that the picking personnel can pick within the time difference range corresponding to the quantity of the orders to be processed.
  • the configuration module 63 is configured to determine the product of the time difference and the work efficiency of the picking personnel, and the corresponding quantity of orders to be processed, as the number of virtual slots configured for the workstations corresponding to the picking personnel.
  • the order distribution device provided in the embodiment of the present application can be used to implement the technical solution of the order distribution method in the above-mentioned embodiment, and the implementation principle and technical effect thereof are similar, and are not repeated here.
  • each module of the above apparatus is only a division of logical functions, and may be fully or partially integrated into a physical entity in actual implementation, or may be physically separated.
  • these modules can all be implemented in the form of software calling through processing elements; they can also all be implemented in hardware; some modules can also be implemented in the form of calling software through processing elements, and some modules can be implemented in hardware.
  • the allocation module 62 and the configuration module 63 may be separately established processing elements, or may be integrated in a certain chip of the above-mentioned device to be implemented, in addition, they may also be stored in the memory of the above-mentioned device in the form of program codes, and the above-mentioned device A certain processing element of the device calls and executes the functions of the above allocation module 62 and configuration module 63 .
  • the implementation of other modules is similar.
  • all or part of these modules can be integrated together, and can also be implemented independently.
  • the processing element here may be an integrated circuit with signal processing capability.
  • each step of the above-mentioned method or each of the above-mentioned modules can be completed by an integrated logic circuit of hardware in the processor element or an instruction in the form of software.
  • FIG. 7 is a schematic structural diagram of a computer device provided by an embodiment of the present application.
  • the computer device may include: a processor 71 , a memory 72 and a transceiver 73 .
  • the processor 71 executes the computer-executed instructions stored in the memory, so that the processor 71 executes the solutions in the above-described embodiments.
  • the processor 71 can be a general-purpose processor, including a central processing unit CPU, a network processor (NP), etc.; it can also be a digital signal processor DSP, an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable Logic devices, discrete gate or transistor logic devices, discrete hardware components.
  • the memory 72 is connected to the processor 71 through a system bus and performs mutual communication, and the memory 72 is used for storing computer program instructions.
  • the transceiver 73 can be used to acquire preset images and images to be detected.
  • the system bus may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus or the like.
  • PCI peripheral component interconnect
  • EISA extended industry standard architecture
  • the system bus can be divided into address bus, data bus, control bus and so on. For ease of presentation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.
  • Transceivers are used to enable communication between the database access device and other computers (eg, clients, read-write libraries, and read-only libraries).
  • Memory may include random access memory (RAM), and may also include non-volatile memory (non-volatile memory).
  • the computer equipment provided in the embodiments of the present application can be used to implement the technical solutions of the order distribution methods in the above embodiments, and the implementation principles and technical effects thereof are similar, and are not repeated here.
  • the embodiment of the present application further provides a chip for running instructions, and the chip is used to execute the technical solution of the order allocation method in the above embodiment.
  • Embodiments of the present application further provide a computer-readable storage medium, where computer instructions are stored in the computer-readable storage medium, and when the computer instructions are executed on a computer, the computer executes the technical solutions of the order distribution methods of the foregoing embodiments.
  • Embodiments of the present application further provide a computer program product, where the computer program product includes a computer program, which is stored in a computer-readable storage medium, at least one processor can read the computer program from the computer-readable storage medium, and at least one processor When the computer program is executed, the technical solution of the order distribution method in the above embodiment can be realized.

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Abstract

本申请提供了一种订单分配方法、装置、设备及存储介质，其中，该方法包括：获取多个待处理订单；获取各个拣选工作站的虚拟槽口的数量；其中，每个拣选工作站的虚拟槽口的数量是根据预设配置规则配置的，用于指示该拣选工作站能够处理的待处理订单的数量；根据各个拣选工作站的虚拟槽口的数量，将多个待处理订单分配至各个拣选工作站。该方案中，由于每个拣选工作站的虚拟槽口的数量是根据预设配置规则配置的，因此，使得每个拣选工作站的虚拟槽口的数量是动态配置的，解决了拣选工作站处理的订单任务量是固定的，造成拣选效率低的问题。

Description

订单分配方法、装置、设备及存储介质
本申请要求于2021年03月31日提交中国专利局、申请号为202110350800.6、申请名称为“订单分配方法、装置、设备及存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及智能仓储技术领域，尤其涉及一种订单分配方法、装置、设备及存储介质。
背景技术
随着电子商务的发展，对于仓储的智能化要求也越来越高。在仓储中，是以工作站为单位进行工作，对于一个工作站而言，播种墙起着很重要的作用。
播种墙是包括多个槽口的货架，其中，每个槽口对应一个或多个订单，用于放置该订单对应的货物。在播种过程中，仓储管理系统(WMS)采用批量拣选和订单合并的方法，将来自多个订单的订单进行集合，重新形成多个目标订单。之后，拣选系统把每个目标订单所需的货物从仓库拣选出来，再将该目标订单所需的货物播种到播种墙对应的槽口。
对于播种墙而言，槽口的数量与其能够处理的订单数量相关，即播种墙有几个槽口，该拣选工作站就只可以接固定数量的订单。如此，拣选工作站需要处理的订单任务量是固定的。
发明内容
本申请提供一种订单分配方法、装置、设备及存储介质，用以解决拣选工作站处理的订单任务量是固定的问题。
第一方面，本申请实施例提供一种订单分配方法，包括：获取多个待处理订单；获取各个拣选工作站的虚拟槽口的数量；其中，每个拣选工作站的虚拟槽口的数量是根据预设配置规则配置的，用于指示该拣选工作站能够处理的待处理订单的数量；根据各个拣选工作站的虚拟槽口的数量，将所述 多个待处理订单分配至各个拣选工作站。
在第一方面的一种可能的设计中，各个拣选工作站的虚拟槽口的数量相同或者不相同。
在第一方面的另种可能的设计中，还包括：根据预设配置规则对各个拣选工作站配置虚拟槽口的数量。
在第一方面的一种可能的设计中，预设配置规则包括：根据各个拣选工作站的拣选效率，或者多个待处理订单中相同库存保有单位的重复率，或者拣选人员的下线时间，或者拣货机器人的数量，对所述各个拣选工作站配置虚拟槽口的数量。
在第一方面的另一种可能的设计中，预设配置规则包括：根据如下至少两项配置参数对各个拣选工作站配置虚拟槽口的数量：各个拣选工作站的拣选效率；多个待处理订单中相同库存保有单位的重复率；拣选人员的下线时间；拣货机器人的数量；其中，每一项配置参数对应一个配置结果；将每个拣选工作站的至少两个配置结果的平均值，或者将至少两个配置结果中的最大值作为所述拣选工作站的虚拟槽口的数量。
在第一方面的一种可能的设计中，根据预设配置规则对各个拣选工作站配置虚拟槽口的数量，包括：获取仓储系统内各个拣选工作站的拣选效率；根据所述各个拣选工作站的拣选效率，对所述各个拣选工作站配置虚拟槽口的数量；其中，每个拣选工作站配置的虚拟槽口的数量，与该拣选工作站的拣选效率正相关。
可选的，所述根据所述各个拣选工作站的拣选效率，对所述各个拣选工作站配置虚拟槽口的数量，包括：若各个拣选工作站的拣选效率相同，则对所述各个拣选工作站配置相同数量的虚拟槽口。
可选的，所述根据所述各个拣选工作站的拣选效率，对所述各个拣选工作站配置虚拟槽口的数量，包括：若各个拣选工作站的拣选效率不同，则确定各个拣选工作站的拣选效率之和，得到总拣选效率；确定各个拣选工作站的拣选效率与所述总拣选效率的比值；根据所述各个拣选工作站的拣选效率与所述总拣选效率的比值，以及所述多个待处理订单的数量，对所述各个拣选工作站配置虚拟槽口的数量；其中，每个拣选工作站的配置的虚拟槽口的数量，为该拣选工作站的拣选效率与所述总拣选效率的比值，和总订单的数 量的乘积，所述总订单包括所述多个待处理订单和所有拣选工作站的已分配订单。
可选的，所述根据所述各个拣选工作站的拣选效率，对所述各个拣选工作站配置虚拟槽口的数量，包括：若各个拣选工作站的拣选效率不同，且当前拣选工作站的拣选效率低于预设的拣选效率阈值，则对所述当前拣选工作站配置第一数量的虚拟槽口；若各个拣选工作站的拣选效率不同，且当前拣选工作站的拣选效率高于或等于预设的拣选效率阈值，则对所述当前拣选工作站配置第二数量的虚拟槽口；其中，所述第二数量大于所述第一数量。
在第一方面的另一种可能的设计中，所述根据预设配置规则对各个拣选工作站配置虚拟槽口的数量，包括：确定所述多个待处理订单中，具有相同库存保有单位的待处理订单的数量；根据所述多个待处理订单中，具有相同库存保有单位的待处理订单的数量，与各个拣选工作站已分配订单的数量，对各个拣选工作站配置虚拟槽口的数量。
具体的，所述根据所述多个待处理订单中，具有相同库存保有单位的待处理订单的数量，与各个拣选工作站已分配订单的数量，对各个拣选工作站配置虚拟槽口的数量，包括：确定所述多个待处理订单中库存保有单位的重复率；将最大重复率的库存保有单位对应的待处理订单的数量，与各个拣选工作站已分配订单的数量之和，确定为所述各个拣选工作站的虚拟槽口的数量，其中，每个拣选工作站配置的虚拟槽口的数量，为所述多个待处理订单中具有相同库存保有单位的待处理订单的数量，与该拣选工作站的已分配订单的数量之和。
在第一方面的另一种可能的设计中，所述根据所述多个待处理订单中，具有相同库存保有单位的待处理订单的数量，与各个拣选工作站已分配订单的数量，对各个拣选工作站配置虚拟槽口的数量，包括：从所述多个待处理订单中，对所述拣选工作站分配一张订单，作为目标订单；确定所述多个待处理订单中其余待处理订单，与所述目标订单中库有保有单位的重复率；将最大重复率的库存保有单位对应的待处理订单的数量，与当前拣选工作站已分配订单的数量之和，确定为所述拣选工作站的虚拟槽口的数量。
在第一方面的又一种可能的设计中，所述根据预设配置规则对各个拣选工作站配置虚拟槽口的数量，包括：根据所述拣选机器人的总数量和所述拣 选工作站的数量，确定每个拣选工作站对应的拣选机器人的数量；其中，每个拣选工作站的虚拟槽口数量小于或等于该拣选工作站对应的拣选机器人的数量，所述拣选机器人用于将拣选的货物搬运至下一作业流程的目的地。
在第一方面的又一种可能的设计中，所述根据预设配置规则对各个拣选工作站配置虚拟槽口的数量，包括：确定当前时间和预设时间之间的时间差，所述预设时间根据所述工作站的拣选人员的下线时间确定；根据所述时间差和所述拣选人员的工作效率，对拣选人员对应的工作站配置第三数量的虚拟槽口；所述拣选人员的工作效率为所述拣选人员在单位时间内能够拣选的货物数量；其中，所述第三数量为所述拣选人员在所述时间差范围内能够拣选的货物数量对应待处理订单的数量。
具体的，所述根据所述时间差和所述拣选人员的工作效率，对所述拣选人员对应的工作站配置第三数量的虚拟槽口，包括：将时间差和所述拣选人员的工作效率的乘积，对应的待处理订单的数量，确定为对拣选人员对应的工作站配置的虚拟槽口的数量。
第二方面，本申请实施例提供一种订单分配装置，包括：获取模块，用于获取多个待处理订单；所述获取模块，还用于获取各个拣选工作站的虚拟槽口的数量；其中，每个拣选工作站的虚拟槽口的数量是根据预设配置规则配置的，用于指示该拣选工作站能够处理的待处理订单的数量；分配模块，用于根据对各个拣选工作站配置的虚拟槽口的数量，将所述多个待处理订单分配至各个拣选工作站。
在第二方面的一种可能的设计中，各个拣选工作站的虚拟槽口的数量相同或者不相同。
在第二方面的另种可能的设计中，还包括：配置模块，用于根据预设配置规则对各个拣选工作站配置虚拟槽口的数量。
在第二方面的一种可能的设计中，预设配置规则包括：根据各个拣选工作站的拣选效率，或者多个待处理订单中相同库存保有单位的重复率，或者拣选人员的下线时间，或者拣货机器人的数量，对所述各个拣选工作站配置虚拟槽口的数量。
在第二方面的另一种可能的设计中，预设配置规则包括：根据如下至少两项配置参数对各个拣选工作站配置虚拟槽口的数量：各个拣选工作站的拣 选效率；多个待处理订单中相同库存保有单位的重复率；拣选人员的下线时间；拣货机器人的数量；其中，每一项配置参数对应一个配置结果；将每个拣选工作站的至少两个配置结果的平均值，或者将至少两个配置结果中的最大值作为所述拣选工作站的虚拟槽口的数量。
在第二方面的一种可能的设计中，配置模块，具体用于：获取仓储系统内各个拣选工作站的拣选效率；根据所述各个拣选工作站的拣选效率，对所述各个拣选工作站配置虚拟槽口的数量；其中，每个拣选工作站配置的虚拟槽口的数量，与该拣选工作站的拣选效率正相关。
可选的，配置模块，具体用于：若各个拣选工作站的拣选效率相同，则对所述各个拣选工作站配置相同数量的虚拟槽口。
可选的，配置模块，具体用于：若各个拣选工作站的拣选效率不同，则确定各个拣选工作站的拣选效率之和，得到总拣选效率；确定各个拣选工作站的拣选效率与所述总拣选效率的比值；根据所述各个拣选工作站的拣选效率与所述总拣选效率的比值，以及所述总订单的数量，对所述各个拣选工作站配置虚拟槽口的数量，所述总订单包括所述多个待处理订单和所有拣选工作站的已分配订单；其中，每个拣选工作站的配置的虚拟槽口的数量，为该拣选工作站的拣选效率与所述总拣选效率的比值，和总订单的数量的乘积。
可选的，配置模块，具体用于：若各个拣选工作站的拣选效率不同，且当前拣选工作站的拣选效率低于预设的拣选效率阈值，则对所述当前拣选工作站配置第一数量的虚拟槽口；若各个拣选工作站的拣选效率不同，且当前拣选工作站的拣选效率高于或等于预设的拣选效率阈值，则对所述当前拣选工作站配置第二数量的虚拟槽口；其中，所述第二数量大于所述第一数量。
在第二方面的另一种可能的设计中，配置模块，具体用于：确定所述多个待处理订单中，具有相同库存保有单位的待处理订单的数量；根据所述多个待处理订单中，具有相同库存保有单位的待处理订单的数量，与各个拣选工作站已分配订单的数量，对各个拣选工作站配置虚拟槽口的数量。
具体的，配置模块，用于确定所述多个待处理订单中库存保有单位的重复率；将最大重复率的库存保有单位对应的待处理订单的数量，与各个拣选工作站已分配订单的数量之和，确定为所述各个拣选工作站的虚拟槽口的数量，其中，每个拣选工作站配置的虚拟槽口的数量，为所述多个待处理订单 中具有相同库存保有单位的待处理订单的数量，与该拣选工作站的已分配订单的数量之和。
在第二方面的另一种可能的设计中，配置模块，具体用于：从所述多个待处理订单中，对所述拣选工作站分配一张订单，作为目标订单；确定所述多个待处理订单中其余待处理订单，与所述目标订单中库有保有单位的重复率；将最大重复率的库存保有单位对应的待处理订单的数量，与当前拣选工作站已分配订单的数量之和，确定为所述拣选工作站的虚拟槽口的数量。
在第二方面的又一种可能的设计中，配置模块，具体用于：根据所述拣选机器人的总数量和所述拣选工作站的数量，确定每个拣选工作站对应的拣选机器人的数量；其中，每个拣选工作站的虚拟槽口数量小于或等于该拣选工作站对应的拣选机器人的数量，所述拣选机器人用于将拣选的货物搬运至下一作业流程的目的地。
在第二方面的又一种可能的设计中，配置模块，具体用于：确定当前时间和预设时间之间的时间差，所述预设时间根据所述工作站的拣选人员的下线时间确定；根据所述时间差和所述拣选人员的工作效率，对拣选人员对应的工作站配置第三数量的虚拟槽口；所述拣选人员的工作效率为所述拣选人员在单位时间内能够拣选的货物数量；其中，所述第三数量为所述拣选人员在所述时间差范围内能够拣选的货物数量对应待处理订单的数量。
具体的，配置模块，用于将时间差和所述拣选人员的工作效率的乘积，对应的待处理订单的数量，确定为对拣选人员对应的工作站配置的虚拟槽口的数量。
第三方面，本申请提供一种计算机设备，包括：处理器、存储器及收发器；
所述存储器存储计算机执行指令；
所述处理器执行所述计算机程序指令时实现第一方面以及各可能设计提供的订单分配方法。
第四方面，本申请提供一种计算机可读存储介质，所述计算机可读存储介质中存储有计算机程序指令，当所述计算机程序指令被处理器执行时用于实现第一方面以及各可能设计提供的订单分配方法。
第五方面，本申请实施例提供一种计算机程序产品，包括计算机程序， 所述计算机程序被处理器执行时用于实现第一方面以及各可能设计提供的订单分配方法。
本申请实施例提供了一种订单分配方法、装置、设备及存储介质，在该方法中，通过获取多个待处理订单；获取各个拣选工作站的虚拟槽口的数量；其中，每个拣选工作站的虚拟槽口的数量是根据预设配置规则配置的，用于指示该拣选工作站能够处理的待处理订单的数量；根据各个拣选工作站的虚拟槽口的数量，将多个待处理订单分配至各个拣选工作站。该方案中，由于每个拣选工作站的虚拟槽口的数量是根据预设配置规则配置的，因此，使得每个拣选工作站的虚拟槽口的数量是动态配置的，解决了拣选工作站处理的订单任务量是固定的问题。
附图说明
此处的附图被并入说明书中并构成本说明书的一部分，示出了符合本申请的实施例，并与说明书一起用于解释本申请的原理。
图1A是本申请实施例提供的智能仓储的示意图；
图1B是相关技术中智能仓储的示意图；
图2为本申请实施例提供的订单分配方法实施例一的流程图；
图3为本申请实施例提供的订单分配方法实施例二的流程图；
图4为本申请实施例提供的订单分配方法实施例三的流程图；
图4A为本申请实施例提供的一种实施方式的示例图；
图4B为本申请实施例提供的另一种实施方式的示例图；
图5为本申请实施例提供的订单分配方法实施例四的流程图；
图6为本申请实施例提供的订单分配装置的结构示意图；
图7为本申请实施例提供的计算机设备的结构示意图。
通过上述附图，已示出本申请明确的实施例，后文中将有更详细的描述。这些附图和文字描述并不是为了通过任何方式限制本申请构思的范围，而是通过参考特定实施例为本领域技术人员说明本申请的概念。
具体实施方式
为使本申请实施例的目的、技术方案和优点更加清楚，下面将结合本申 请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
图1A是本申请实施例提供的智能仓储的示意图。如图1A所示，包括控制设备11、仓库12、搬运机器人13、拣货工作站14、拣选机器人15和打包站16；其中，控制设备11可以是服务器、终端等，控制设备11上可以安装有仓储管理系统。
控制设备11接收订单。控制设备11上安装的仓库管理系统对每批次接收到的订单所包含的商品进行合并，组成波次，并确定仓库12中包含订单中商品的料箱，再通过搬运机器人13将料箱搬运至拣货工作站14进行分拣，分拣后的货物通过拣选机器人15运输至分拣格口16，然后打包出库。
在相关技术中，如图1B所示，包括控制设备21、仓库22、搬运机器人23、拣货工作站24、拣选人员251、拣选人员252和播种墙26；每个工作站对应一个或多个播种墙26，搬运机器人23将货物或者料箱搬运至拣货工作站24之后，通过播种墙26完成货物的分拣。即：拣选人员251对运输到工作站的料箱用条码枪逐个扫描其条形码，并依照播种墙槽口的亮灯指示，把拣选出的货物播放到亮灯的槽口上。当播种墙背面亮灯指示并显示订单货品数时，表明该槽口的订单货品已拣齐，播种墙背面的拣选人员252就可以将亮灯槽口的订单进行二次分拣或者复核打包。
在通过分拣工作站进行货物分拣的过程中，播种墙的槽口是实体槽口，且数量是固定的，所以，一个工作站最多能够接收固定数量的订单。因此，导致搬运机器人可能来回搬运同一个料箱多次，造成拣选效率低。以牙膏料箱为例，若一个播种墙对应10个槽口，则该播种墙可以接收的最大订单数量是10个。若WMS接收到20个订单，该20个订单都需要牙膏，那么搬运机器人从仓库将牙膏的料箱搬运至播种墙完成10个订单之后，需要将该料箱再搬运回仓库，之后，WMS系统再给该播种墙下发另外10个订单，那么搬运机器人就需要再搬运一次该牙膏的料箱，如此，同一个料箱就需要搬运多次，增加时间成本，导致拣选效率低。
本申请针对上述技术问题，发明人的技术构思过程如下：使用虚拟槽 口代替播种墙的实体槽口，根据每个工作站的工作能力，即能够接收的最大订单数量对虚拟槽口的数量进行配置，如此，每个工作站的工作能力是会动态变化的，因而可以实现动态配置虚拟槽口的数量，进而使每个工作站能够接收的订单数量可以灵活调配。
下面，通过具体实施例对本申请的技术方案进行详细说明。需要说明的是，下面这几个具体的实施例可以相互结合，对于相同或相似的概念或过程可能在某些实施例中不再赘述。
图2为本申请实施例提供的订单分配方法实施例一的流程图。如图2所示，该订单分配方法可以包括如下步骤：
步骤S201、获取多个待处理订单。
其中，多个待处理订单可以是仓库管理系统在一段时间内接收到的用户设备发送的订单。例如，仓库管理系统每天接收到的用户设备发送的订单。
步骤S202、获取各个拣选工作站的虚拟槽口的数量；其中，每个拣选工作站的虚拟槽口的数量是根据预设配置规则配置的，用于指示该拣选工作站能够处理的待处理订单的数量。
本实施例中没有播种墙和实体槽口，通过虚拟槽口代替实体槽口，并根据预设配置规则对各个拣选工作站的虚拟槽口的数量进行动态配置，虚拟槽口的数量可以根据各个拣选工作站能够处理的订单数量确定。对于单个拣选工作站而言，该拣选工作站配置的虚拟槽口的数量，即为该拣选工作站一次性能够同时处理的订单数量。
可选的，本实施例可以根据预设配置规则将每个拣选工作站的虚拟槽口的数量预先配置好，并存储在控制设备中。从而在需要进行订单分配时，直接获取对各个拣选工作站配置的虚拟槽口的数量，并进行订单分配。
可选的，本实施例还可以是实时地对每个拣选工作站的虚拟槽口的数量进行配置。即：可以是在获取到多个待处理订单之后，根据预设配置规则对每个拣选工作站的虚拟槽口的数量进行配置。也可以是在获取到多个待处理订单之前，根据预设配置规则对每个拣选工作站的虚拟槽口的数量进行配置。也可以是每个时间段按照预设配置规则进行更新等，在此不做限定。
应当理解，本实施例中，各个工作站的虚拟槽口数量的配置过程可以执行一次或多次；若执行一次，则每次订单分配过程都使用该次配置好的虚拟 槽口数量。若执行多次，则是对每次订单分配过程，都匹配当前的虚拟槽口数量。
步骤S203、根据各个拣选工作站的虚拟槽口的数量，将多个待处理订单分配至各个拣选工作站。
通常情况下，一个待处理订单对应一个虚拟槽口。而在一些场景中，可能会存在多个待处理订单对应一个虚拟槽口的情况。例如，多个待处理订单中有多个订单属于单品单件类型，即一个待处理订单包括一个子订单，该子订单包括一件商品，为了最大化利用虚拟槽口，可以将该种类型的待处理订单分配给同一个虚拟槽口。
本实施例中，虚拟槽口可以通过拣选机器人实现，其含义是实体槽口存储货物的功能可以由拣选机器人实现。其中，拣选机器人可以是AGV(Automated Guided Vehicle)小车、顶升式机器人、翻斗式机器人。具体的，搬运机器人将料箱搬运至拣选工作站之后，工作人员将本拣选工作站所分配的订单对应的货物放置在拣选机器人的托盘上，拣选机器人将货物运输至下一作业流程的目的地，例如，运输至打包出库的目的地进行打包出库。之后，再返回拣选工作站，接收该拣选工作站分配的订单对应的其他货物，并运输至下一作业流程的目的地。如此反复多次，可完成拣选工作站所分配的订单对应的货物。
应当理解的是，每个拣选工作站对应至少一个拣选机器人，该至少一个拣选机器人每次接收分配给该拣选工作站的订单中的至少一件货物。
仍然以上述实施例介绍的牙膏料箱为例，相较于实体槽口的播种墙来说，在拣选工作站的工作能力范围内，本实施例可以实现一次性对拣选工作站配置20个虚拟槽口，那么搬运机器人在将牙膏料箱搬运至拣选工作站之后，该拣选工作站就可以一次性将20个订单中对牙膏的需求拣选完成，搬运机器人只需要搬运一次牙膏料箱即可，不再需要来回搬运料箱，因此，能够提高一个料箱对多个待处理订单的命中率，从而减少搬运时间，提高拣选效率。
本实施例的订单分配方法，通过获取多个待处理订单，和获取各个拣选工作站的虚拟槽口的数量；其中，每个拣选工作站的虚拟槽口的数量是根据预设配置规则配置的，用于指示该拣选工作站能够处理的待处理订单的数量；并根据各个拣选工作站的虚拟槽口的数量，将多个待处理订单分配至各个拣 选工作站。该方案中，由于每个拣选工作站的虚拟槽口的数量是根据预设配置规则配置的，因此，使得每个拣选工作站的虚拟槽口的数量是动态配置的，解决了播种墙处理的订单任务量是固定的，导致拣选效率低的问题。
在上述实施例的基础上，各个拣选工作站的虚拟槽口的数量可以相同，也可以不相同。相应地，预设配置规则可以包括：对各个拣选工作站配置相同或者不同数量的虚拟槽口。
在订单分配过程中，各个拣选工作站的虚拟槽口的数量，决定了该拣选工作站能够接收多少个待处理订单。参考前述实施例介绍，拣选工作站能够接收的待处理订单的数量，会影响同一个料箱命中的待处理订单的数量。那么若单工作站能够接收的待处理订单的数量越多，则同一个料箱命中的待处理订单的数量也会越多。进而就会减少搬运机器人搬运料箱的次数，从而提高拣选效率。因而，配置各个拣选工作站的虚拟槽口的数量是关键。在上述实施例的基础上，本实施例的订单分配方法还包括如下步骤：根据预设配置规则对各个拣选工作站配置虚拟槽口的数量。
可选的，预设配置规则包括：根据各个拣选工作站的拣选效率、多个待处理订单中相同库存保有单位的重复率、拣选人员的下线时间或者机器人的数量，对各个拣选工作站配置虚拟槽口的数量。本实施例中，可以单独根据各个拣选工作站的拣选效率对每个拣选工作站配置虚拟槽口的数量，也可以单独根据多个待处理订单中相同库存保有单位的重复率对每个拣选工作站配置虚拟槽口的数量，还可以单独根据拣选人员的下线时间对各个拣选工作站配置虚拟槽口的数量，还可以单独根据机器人的数量对各个拣选工作站配置虚拟槽口的数量。
可选的，预设配置规则还可以包括：根据如下至少两项配置参数对各个拣选工作站配置虚拟槽口的数量：
1)各个拣选工作站的拣选效率；
2)多个待处理订单中相同库存保有单位的重复率；
3)拣选人员的下线时间；
4)拣货机器人的数量；
其中，上述每一项配置参数对应一个配置结果；
将每个拣选工作站的至少两个配置结果的平均值作为拣选工作站的虚拟 槽口的数量，或者将每个拣选工作站的至少两个配置结果中的最大值作为该拣选工作站的虚拟槽口的数量。
举例来说，分别根据各个拣选工作站的拣选效率、多个待处理订单中相同库存保有单位的重复率、拣选人员的下线时间和机器人的数量，对各个拣选工作站配置虚拟槽口的数量，则每个拣选工作站可以得到四个配置结果，将该四个配置结果的平均值作为该拣选工作站的虚拟槽口的数量。
下面将对根据各个拣选工作站的拣选效率、多个待处理订单中相同库存保有单位的重复率、拣选人员的下线时间和机器人的数量中的每一项，对各个拣选工作站配置虚拟槽口的数量进行详细说明：
在图2的基础上，图3为本申请实施例提供的订单分配方法实施例二的流程图。下面结合图3，对本申请实施例提供的订单分配方法进行详细说明。如图3所示，包括如下步骤：
步骤S301、获取仓储系统内各个拣选工作站的拣选效率。
其中，拣选工作站的拣选效率，为该拣选工作站在单位时间内能够拣选的货物数量。本实施例可以预先将各个拣选工作站的拣选效率确定好，并存储在控制设备中。其中，确定各个拣选工作站的拣选效率，包括：获取各个工作站每天拣选的货物数量；根据各个工作站每天拣选的货物数量，计算各个拣选工作站在单位时间内拣选的货物数量，得到各个拣选工作站的拣选效率。需要说明的是，对于各个拣选工作站而言，相同的拣选工作站不同的拣选人员，拣选效率不同；或者，不同的拣选工作站，若部分拣选工作站采用人工拣选，部分拣选工作站采用机械拣选，则人工拣选和机械拣选的效率也不同。
示例性地，若某个拣选工作站每天能够拣选的货物数量为N，则该拣选工作站的拣选效率＝N/24，单位为：件/小时。
步骤S302、根据各个拣选工作站的拣选效率，对各个拣选工作站配置虚拟槽口的数量。
其中，每个拣选工作站配置的虚拟槽口的数量，与该拣选工作站的拣选效率正相关。正相关可以理解为拣选工作站的拣选效率越高，则该拣选工作站的虚拟槽口的数量越多；反之，拣选工作站的拣选效率越低，则该拣选工作站的虚拟槽口的数量越少。
其中，步骤S302可以通过如下至少一种实施方式实现：
在一种可选的实施方式中，步骤S302的实现可以包括如下步骤：若各个拣选工作站的拣选效率相同，则对各个拣选工作站配置相同数量的虚拟槽口；若各个拣选工作站的拣选效率不同，则对各个拣选工作站配置不同数量的虚拟槽口。
在另一种可选的实施方式中，步骤S302的实现可以包括如下步骤：
步骤a1、若各个拣选工作站的拣选效率不同，则确定各个拣选工作站的拣选效率之和，得到总拣选效率。
步骤a2、确定各个拣选工作站的拣选效率与总拣选效率的比值。
步骤a3、根据各个拣选工作站的拣选效率与总拣选效率的比值，和总订单的数量，对各个拣选工作站配置虚拟槽口的数量，总订单包括多个待处理订单和所有拣选工作站的已分配订单。
其中，每个拣选工作站的配置的虚拟槽口的数量，为该拣选工作站的拣选效率与总拣选效率的比值，和总订单的数量的乘积。
本实施方式中，每个拣选工作站的虚拟槽口的数量可以表示为如下公式：
Figure PCTCN2022079744-appb-000001
式中，e i为编号为i的拣选工作站的拣选效率；M为拣选工作站的总数量；D为总订单的数量；A i为编号为i的拣选工作站的虚拟槽口的数量。
在又一种可选的实施方式中，步骤S302的实现可以包括如下步骤：
步骤b1、若各个拣选工作站的拣选效率不同，且当前拣选工作站的拣选效率低于预设的拣选效率阈值，则对当前拣选工作站配置第一数量的虚拟槽口。
步骤b2、若各个拣选工作站的拣选效率不同，且当前拣选工作站的拣选效率高于或等于预设的拣选效率阈值，则对当前拣选工作站配置第二数量的虚拟槽口；其中，第二数量大于第一数量。
本实施方式中，可以设置一预设的拣选效率阈值，将各个拣选工作站划分为拣选效率高的工作站和拣选效率低的工作站，从而对拣选效率高的工作站较多数量的虚拟槽口，对拣选效率低的工作站配置较少数量的虚拟 槽口。从而使得各个工作站的拣选效率在整体上达到均衡。
可选的，预设的拣选效率阈值可以根据各个工作站的拣选效率平均值确定。应当理解，根据各个工作站的拣选效率平均值确定预设的拣选效率阈值为示例性说明，不对本申请进行限定。本领域技术人员可以根据实际需求设置预设的拣选效率阈值。例如，取最高拣选效率和最低拣选效率的平均值。
在图2的基础上，图4为本申请实施例提供的订单分配方法实施例三的流程图。下面结合图4，对本申请实施例提供的订单分配方法进行详细说明。如图4所示，包括如下步骤：
步骤S401、确定多个待处理订单中，具有相同库存保有单位的待处理订单的数量。
其中，库存保有单位(SKU)是物理上不可分割的最小存货单元，可以是以件、盒、托盘等为单位。以服装为例，相同款式的衣服，具有颜色和尺码两个属性，则一种颜色和一个尺码可以对应一个SKU。例如，某一款式的衣服具有黑色和白色两种颜色，以及S、M、L三种尺码，则黑色S码可以是一个SKU，黑色M码是一个SKU。
步骤S402、根据多个待处理订单中，具有相同库存保有单位的待处理订单的数量，与各个拣选工作站已分配订单的数量，对各个拣选工作站配置虚拟槽口的数量。
其中，步骤S402至少包括如下两种实施方式：
在一种可选的实施方式中，根据多个待处理订单中，具有相同库存保有单位的待处理订单的数量，与各个拣选工作站已分配订单的数量，对各个拣选工作站配置虚拟槽口的数量，包括：
步骤c1、确定多个待处理订单中库存保有单位的重复率。
其中，重复率可以根据如下方法定义：多个待处理订单的数量为M，该M个待处理订单中，具有相同库存保有单位的待处理订单的数量是m个，则该库存保有单位的重复率为：m/M。
举例来说，当前有100个待处理订单的数量，该100个待处理订单中共包括10种SKU，其中1种SKU在50个待处理订单都出现了，则该SKU的重复率为50/100＝50％。
步骤c2、将最大重复率的库存保有单位对应的待处理订单的数量，与各个拣选工作站已分配订单的数量之和，确定为各个拣选工作站的虚拟槽口的数量，其中，每个拣选工作站配置的虚拟槽口的数量，为多个待处理订单中具有相同库存保有单位的待处理订单的数量，与该拣选工作站的已分配订单的数量之和。
具体的，本实施例可以将各个拣选工作站的虚拟槽口的数量，均设置为最大重复率的库存保有单位对应的待处理订单的数量，与各个拣选工作站已分配订单的数量之和。举例来说，各个拣选工作站包括拣选工作站1、拣选工作站2和拣选工作站3；拣选工作站1、拣选工作站2和拣选工作站3的已分配订单的数量分别为10、20和30；其中，多个待处理订单中，最大重复率的库存保有单位对应的待处理订单的数量为30，则拣选工作站1的虚拟槽口的数量为40，拣选工作站2的虚拟槽口的数量为50，拣选工作站3的虚拟槽口的数量为60。
如图4A所示，多个待处理订单中总共包括n种SKU，则本实施例需要确定每个SKU的重复率，之后每个拣选工作站已分配订单的数量，与SKU1～SKUn中的最大重复率对应的待处理订单的数量之和，确定为对应的拣选工作站的虚拟槽口的数量。
举例来说，假设有100个待处理订单，该100个待处理订单中，有30个待处理订单中都包括A款式的黑色S码衣服，则A款式的黑色S码衣服的重复率为30％，且该100个待处理订单中，有10个待处理订单中都包括A款式的黑色M码衣服，则A款式的黑色S码衣服的重复率为10％。
若当前拣选工作站已分配订单的数量为10，则本实施例是根据重复率为30％的SKU对应的待处理订单的数量，以及当前拣选工作站已分配订单的数量为10，将各个拣选工作站的虚拟槽口的数量均设置为40。
在另一种可选的实施方式中，根据多个待处理订单中，具有相同库存保有单位的待处理订单的数量，与各个拣选工作站已分配订单的数量，对各个拣选工作站配置虚拟槽口的数量，包括：
步骤d1、从多个待处理订单中，对拣选工作站分配一张订单，作为目标订单。
步骤d2、确定多个待处理订单中其余待处理订单，与目标订单中库有保 有单位的重复率。
步骤d3、将最大重复率的库存保有单位对应的待处理订单的数量，与各个拣选工作站已分配订单的数量之和，确定为该拣选工作站的虚拟槽口的数量。
举例来说，如图4B所示，假设有100个待处理订单，10个拣选工作站，拣选工作站1的已分配订单的数量为10，则将其中一个待处理订单分配给拣选工作站1之后，再确定其余99个待处理订单与该1个订单中SKU的重复率。由于一个待处理订单中通常包括多个SKU，那么该100个订单中，就会包括多个SKU，则本实施例是确定每个SKU的重复率，关于重复率的计算方式可以参见前述实施例的介绍，此处不再赘述。
若其余99个待处理订单中，有39个订单中都包括SKU1，则SKU1的重复率为40％，有9个订单中都包括SKU2，SKU2的重复率为10％，有49个订单中都包括SKU1，SKU3的重复率为50％，则将SKU3对应的待处理订单的数量49再加上目标订单，以及加上当前拣选工作站已分配的订单数量10，作为对拣选工作站1配置的虚拟槽口的数量60。
本实施例中，根据SKU的重复率配置虚拟槽口的数量，可以保证将相同SKU的待处理订单分配至同一拣选工作站时，该拣选工作站能够接收这些具有相同SKU的待处理订单，并且拣选机器人在搬运料箱时，可以减少行走路径，从而减少搬运时间，进一步提高拣选效率。
在上述实施例的基础上，本申请实施例的订单分配方法还可以包括如下步骤：根据拣选机器人的总数量和拣选工作站的数量，确定每个拣选工作站对应的拣选机器人的数量；其中，每个拣选工作站的虚拟槽口数量小于或等于该拣选工作站对应的拣选机器人的数量，机器人用于将拣选出的货物搬运至下一作业流程的目的地。
本实施例可以是在通过前述实施例的方式确定每个拣选工作站的虚拟槽口的数量的基础上，进一步根据拣选机器人的总数量和拣选工作站的数量，确定每个拣选工作站对应的拣选机器人的数量。也可以是单独根据拣选机器人的总数量和拣选工作站的数量，确定每个拣选工作站对应的拣选机器人的数量。其中，各个拣选工作站对应的拣选机器人的数量之和，小于或等于拣选机器人的总数量。
本实施例中，每个拣选工作站的虚拟槽口数量小于或等于该拣选工作站对应的拣选机器人的数量，可以避免一个拣选工作站内，拣选机器人数量过少，虚拟槽口数量过多，导致拣选机器人不能第一时间接收到拣选货物，而造成拣选货物在工作站堆积的情况。
在图2的基础上，图5为本申请实施例提供的订单分配方法实施例四的流程图。下面结合图5，对本申请实施例提供的订单分配方法进行详细说明。如图5所示，包括如下步骤：
步骤S501、确定当前时间和预设时间之间的时间差，预设时间根据工作站的拣选人员的下线时间确定。
步骤S502、根据时间差和拣选人员的工作效率，对拣选人员对应的拣选工作站配置第三数量的虚拟槽口；拣选人员的工作效率为拣选人员在单位时间内能够拣选的货物数量。其中，第三数量为拣选人员在时间差范围内能够拣选的货物对应的待处理订单的数量。
其中，根据时间差和拣选人员的工作效率，对拣选人员对应的拣货工作站配置第三数量的虚拟槽口，包括：将时间差和拣选人员的工作效率的乘积，对应的待处理订单的数量，确定为对拣选人员对应的工作站配置的虚拟槽口的数量。
举例来说，假设拣选人员的下线时间为18:00，当前时间为17:00，而该拣选人员的拣货效率为40件/小时，则对该拣选人员对应的拣货工作站配置40个虚拟槽口。
本实施例中，通过当前时间、拣选人员的下线时间和拣选人员的工作效率，对该拣选人员对应的拣货工作站配置虚拟槽口的数量，使得可以灵活配置虚拟槽口的数量，保证工作人员准时下线。
可选的，为了保证每个虚拟槽口对应的货物数量的准确性，本实施例的方法还可以包括如下步骤：
步骤f1、接收扫描终端对待处理订单中的货物进行扫描后，发送的拣选完成的信号。
步骤f2、根据拣选完成的信号，对待处理订单中的货物的状态信息进行更新。
步骤f3、在接收到待处理订单中的所有货物的拣选完成的信号后，发送 拣选完成的信号至下一作业流程对应的终端。
本实施例中，搬运机器人将该工作站需要的货物对应的料箱搬运至该工作站区域内，该工作站的拣选人员手持扫描终端将料箱中的货物进行扫描，进而扫描终端会发送拣选完成的信号至控制设备，控制设备将WMS系统中该货物的状态信息更改为拣选完成，待打包出库；控制设备根据分配给该工作站的待处理订单对应的货物和已拣选完成的货物，确定待处理订单对应的货物是否均拣选完成，从而确保该虚拟槽口对应的货物数量的准确性。
在上述订单分配方法实施例的基础上，图6为本申请实施例提供的订单分配装置的结构示意图。如图6所示，该订单分配装置包括：获取模块61和分配模块62。其中，获取模块61，用于获取多个待处理订单；获取模块61，还用于获取各个拣选工作站的虚拟槽口的数量；其中，每个拣选工作站的虚拟槽口的数量是根据预设配置规则配置的，用于指示该拣选工作站能够处理的待处理订单的数量；分配模块62，用于根据各个拣选工作站的虚拟槽口的数量，将所述多个待处理订单分配至各个拣选工作站。
在第二方面的一种可能的设计中，各个拣选工作站的虚拟槽口的数量相同或者不相同。
在第二方面的另种可能的设计中，还包括：配置模块63，用于根据预设配置规则对各个拣选工作站配置虚拟槽口的数量。
在第二方面的一种可能的设计中，预设配置规则包括：根据各个拣选工作站的拣选效率，或者多个待处理订单中相同库存保有单位的重复率，或者拣选人员的下线时间，或者拣货机器人的数量，对所述各个拣选工作站配置虚拟槽口的数量。
在第二方面的另一种可能的设计中，预设配置规则包括：根据如下至少两项配置参数对各个拣选工作站配置虚拟槽口的数量：各个拣选工作站的拣选效率；多个待处理订单中相同库存保有单位的重复率；拣选人员的下线时间；拣货机器人的数量；其中，每一项配置参数对应一个配置结果；将每个拣选工作站的至少两个配置结果的平均值，或者将至少两个配置结果中的最大值作为所述拣选工作站的虚拟槽口的数量。
在第二方面的一种可能的设计中，配置模块63，具体用于：获取仓储系 统内各个拣选工作站的拣选效率；根据所述各个拣选工作站的拣选效率，对所述各个拣选工作站配置虚拟槽口的数量；其中，每个拣选工作站配置的虚拟槽口的数量，与该拣选工作站的拣选效率正相关。
可选的，配置模块63，具体用于：若各个拣选工作站的拣选效率相同，则对所述各个拣选工作站配置相同数量的虚拟槽口。
可选的，配置模块63，具体用于：若各个拣选工作站的拣选效率不同，则确定各个拣选工作站的拣选效率之和，得到总拣选效率；确定各个拣选工作站的拣选效率与所述总拣选效率的比值；根据所述各个拣选工作站的拣选效率与所述总拣选效率的比值，以及所述总订单的数量，对所述各个拣选工作站配置虚拟槽口的数量，所述总订单包括所述多个待处理订单和所有拣选工作站的已分配订单；其中，每个拣选工作站的配置的虚拟槽口的数量，为该拣选工作站的拣选效率与所述总拣选效率的比值，和总订单的数量的乘积。
可选的，配置模块63，具体用于：若各个拣选工作站的拣选效率不同，且当前拣选工作站的拣选效率低于预设的拣选效率阈值，则对所述当前拣选工作站配置第一数量的虚拟槽口；若各个拣选工作站的拣选效率不同，且当前拣选工作站的拣选效率高于或等于预设的拣选效率阈值，则对所述当前拣选工作站配置第二数量的虚拟槽口；其中，所述第二数量大于所述第一数量。
在第二方面的另一种可能的设计中，配置模块63，具体用于：确定所述多个待处理订单中，具有相同库存保有单位的待处理订单的数量；根据所述多个待处理订单中，具有相同库存保有单位的待处理订单的数量，与各个拣选工作站已分配订单的数量，对各个拣选工作站配置虚拟槽口的数量。
具体的，配置模块63，用于确定所述多个待处理订单中库存保有单位的重复率；将最大重复率的库存保有单位对应的待处理订单的数量，与各个拣选工作站已分配订单的数量之和，确定为所述各个拣选工作站的虚拟槽口的数量，其中，每个拣选工作站配置的虚拟槽口的数量，为所述多个待处理订单中具有相同库存保有单位的待处理订单的数量，与该拣选工作站的已分配订单的数量之和。
在第二方面的另一种可能的设计中，配置模块63，具体用于：从所述多个待处理订单中，对所述拣选工作站分配一张订单，作为目标订单；确定所述多个待处理订单中其余待处理订单，与所述目标订单中库有保有单位的重 复率；将最大重复率的库存保有单位对应的待处理订单的数量，与当前拣选工作站已分配订单的数量之和，确定为所述拣选工作站的虚拟槽口的数量。
在第二方面的又一种可能的设计中，配置模块63，具体用于：根据所述拣选机器人的总数量和所述拣选工作站的数量，确定每个拣选工作站对应的拣选机器人的数量；其中，每个拣选工作站的虚拟槽口数量小于或等于该拣选工作站对应的拣选机器人的数量，所述拣选机器人用于将拣选的货物搬运至下一作业流程的目的地。
在第二方面的又一种可能的设计中，配置模块63，具体用于：确定当前时间和预设时间之间的时间差，所述预设时间根据所述工作站的拣选人员的下线时间确定；根据所述时间差和所述拣选人员的工作效率，对拣选人员对应的工作站配置第三数量的虚拟槽口；所述拣选人员的工作效率为所述拣选人员在单位时间内能够拣选的货物数量；其中，所述第三数量为所述拣选人员在所述时间差范围内能够拣选的货物数量对应待处理订单的数量。
具体的，配置模块63，用于将时间差和所述拣选人员的工作效率的乘积，对应的待处理订单的数量，确定为对拣选人员对应的工作站配置的虚拟槽口的数量。
本申请实施例提供的订单分配装置，可用于执行上述实施例中订单分配方法的技术方案，其实现原理和技术效果类似，在此不再赘述。
需要说明的是，应理解以上装置的各个模块的划分仅仅是一种逻辑功能的划分，实际实现时可以全部或部分集成到一个物理实体上，也可以物理上分开。且这些模块可以全部以软件通过处理元件调用的形式实现；也可以全部以硬件的形式实现；还可以部分模块通过处理元件调用软件的形式实现，部分模块通过硬件的形式实现。例如，分配模块62、配置模块63可以为单独设立的处理元件，也可以集成在上述装置的某一个芯片中实现，此外，也可以以程序代码的形式存储于上述装置的存储器中，由上述装置的某一个处理元件调用并执行以上分配模块62、配置模块63的功能。其它模块的实现与之类似。此外这些模块全部或部分可以集成在一起，也可以独立实现。这里的处理元件可以是一种集成电路，具有信号的处理能力。在实现过程中，上述方法的各步骤或以上各个模块可以通过处理器元件中的硬件的集成逻辑电路或者软件形式的指令完成。
图7为本申请实施例提供的计算机设备的结构示意图。如图7所示，该计算机设备可以包括：处理器71、存储器72和收发器73。
处理器71执行存储器存储的计算机执行指令，使得处理器71执行上述实施例中的方案。处理器71可以是通用处理器，包括中央处理器CPU、网络处理器(network processor，NP)等；还可以是数字信号处理器DSP、专用集成电路ASIC、现场可编程门阵列FPGA或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。
存储器72通过系统总线与处理器71连接并完成相互间的通信，存储器72用于存储计算机程序指令。
收发器73可以用于获取预设图像以及待检测图像。
系统总线可以是外设部件互连标准(peripheral component interconnect，PCI)总线或扩展工业标准结构(extended industry standard architecture，EISA)总线等。系统总线可以分为地址总线、数据总线、控制总线等。为便于表示，图中仅用一条粗线表示，但并不表示仅有一根总线或一种类型的总线。收发器用于实现数据库访问装置与其他计算机(例如客户端、读写库和只读库)之间的通信。存储器可能包含随机存取存储器(random access memory，RAM)，也可能还包括非易失性存储器(non-volatile memory)。
本申请实施例提供的计算机设备，可用于执行上述实施例中订单分配方法的技术方案，其实现原理和技术效果类似，在此不再赘述。
本申请实施例还提供一种运行指令的芯片，该芯片用于执行上述实施例中订单分配方法的技术方案。
本申请实施例还提供一种计算机可读存储介质，该计算机可读存储介质中存储有计算机指令，当该计算机指令在计算机上运行时，使得计算机执行上述实施例订单分配方法的技术方案。
本申请实施例还提供一种计算机程序产品，该计算机程序产品包括计算机程序，其存储在计算机可读存储介质中，至少一个处理器可以从计算机可读存储介质读取计算机程序，至少一个处理器执行计算机程序时可实现上述实施例中订单分配方法的技术方案。
最后应说明的是：以上各实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述各实施例对本申请进行了详细的说明，本领域的普通 技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的范围。

Claims (19)

  1. 一种订单分配方法，其特征在于，包括：
    获取多个待处理订单；
    获取各个拣选工作站的虚拟槽口的数量；其中，每个拣选工作站的虚拟槽口的数量是根据预设配置规则配置的，用于指示该拣选工作站能够处理的待处理订单的数量；
    根据各个拣选工作站的虚拟槽口的数量，将所述多个待处理订单分配至各个拣选工作站。
  2. 根据权利要求1所述的方法，其特征在于，所述各个拣选工作站的虚拟槽口的数量相同或者不相同。
  3. 根据权利要求2所述的方法，其特征在于，还包括：
    根据预设配置规则对各个拣选工作站配置虚拟槽口的数量。
  4. 根据权利要求3所述的方法，其特征在于，所述预设配置规则包括：根据各个拣选工作站的拣选效率，或者多个待处理订单中相同库存保有单位的重复率，或者拣选人员的下线时间，或者拣货机器人的数量，对所述各个拣选工作站配置虚拟槽口的数量。
  5. 根据权利要求3所述的方法，其特征在于，所述预设配置规则包括：根据如下至少两项配置参数对各个拣选工作站配置虚拟槽口的数量：
    各个拣选工作站的拣选效率；
    多个待处理订单中相同库存保有单位的重复率；
    拣选人员的下线时间；
    拣货机器人的数量；
    其中，每一项配置参数对应一个配置结果；
    将每个拣选工作站的至少两个配置结果的平均值，或者将至少两个配置结果中的最大值作为所述拣选工作站的虚拟槽口的数量。
  6. 根据权利要求4或5所述的方法，其特征在于，所述根据预设配置规则对各个拣选工作站配置虚拟槽口的数量，包括：
    获取仓储系统内各个拣选工作站的拣选效率；
    根据所述各个拣选工作站的拣选效率，对所述各个拣选工作站配置虚拟槽口的数量；
    其中，每个拣选工作站配置的虚拟槽口的数量，与该拣选工作站的拣选效率正相关。
  7. 根据权利要求6所述的方法，其特征在于，所述根据所述各个拣选工作站的拣选效率，对所述各个拣选工作站配置虚拟槽口的数量，包括：
    若各个拣选工作站的拣选效率相同，则对所述各个拣选工作站配置相同数量的虚拟槽口。
  8. 根据权利要求6所述的方法，其特征在于，所述根据所述各个拣选工作站的拣选效率，对所述各个拣选工作站配置虚拟槽口的数量，包括：
    若各个拣选工作站的拣选效率不同，则确定各个拣选工作站的拣选效率之和，得到总拣选效率；
    确定各个拣选工作站的拣选效率与所述总拣选效率的比值；
    根据所述各个拣选工作站的拣选效率与所述总拣选效率的比值，以及所述总订单的数量，对所述各个拣选工作站配置虚拟槽口的数量，所述总订单包括所述多个待处理订单和所有拣选工作站的已分配订单；
    其中，每个拣选工作站的配置的虚拟槽口的数量，为该拣选工作站的拣选效率与所述总拣选效率的比值，和总订单的数量的乘积。
  9. 根据权利要求6所述的方法，其特征在于，所述根据所述各个拣选工作站的拣选效率，对所述各个拣选工作站配置虚拟槽口的数量，包括：
    若各个拣选工作站的拣选效率不同，且当前拣选工作站的拣选效率低于预设的拣选效率阈值，则对所述当前拣选工作站配置第一数量的虚拟槽口；
    若各个拣选工作站的拣选效率不同，且当前拣选工作站的拣选效率高于或等于预设的拣选效率阈值，则对所述当前拣选工作站配置第二数量的虚拟槽口；
    其中，所述第二数量大于所述第一数量。
  10. 根据权利要求4或5所述的方法，其特征在于，所述根据预设配置规则对各个拣选工作站配置虚拟槽口的数量，包括：
    确定所述多个待处理订单中，具有相同库存保有单位的待处理订单的数量；
    根据所述多个待处理订单中，具有相同库存保有单位的待处理订单的数量，与各个拣选工作站的已分配订单的数量，对各个拣选工作站配置虚拟槽 口的数量。
  11. 根据权利要求10所述的方法，其特征在于，所述根据所述多个待处理订单中，具有相同库存保有单位的待处理订单的数量，与各个拣选工作站已分配订单的数量，对各个拣选工作站配置虚拟槽口的数量，包括：
    确定所述多个待处理订单中库存保有单位的重复率；
    将最大重复率的库存保有单位对应的待处理订单的数量，与各个拣选工作站已分配订单的数量之和，确定为所述各个拣选工作站的虚拟槽口的数量，其中，每个拣选工作站配置的虚拟槽口的数量，为所述多个待处理订单中具有相同库存保有单位的待处理订单的数量，与该拣选工作站的已分配订单的数量之和。
  12. 根据权利要求10所述的方法，其特征在于，所述根据所述多个待处理订单中，具有相同库存保有单位的待处理订单的数量，与各个拣选工作站已分配订单的数量，对各个拣选工作站配置虚拟槽口的数量，包括：
    从所述多个待处理订单中，对所述拣选工作站分配一张订单，作为目标订单；
    确定所述多个待处理订单中其余待处理订单，与所述目标订单中库有保有单位的重复率；
    将最大重复率的库存保有单位对应的待处理订单的数量，与当前拣选工作站已分配订单的数量之和，确定为所述拣选工作站的虚拟槽口的数量。
  13. 根据权利要求4或5所述的方法，其特征在于，所述根据预设配置规则对各个拣选工作站配置虚拟槽口的数量，包括：
    根据所述拣选机器人的总数量和所述拣选工作站的数量，确定每个拣选工作站对应的拣选机器人的数量；其中，每个拣选工作站的虚拟槽口数量小于或等于该拣选工作站对应的拣选机器人的数量，所述拣选机器人用于将拣选的货物搬运至下一作业流程的目的地。
  14. 根据权利要求4或5所述的方法，其特征在于，所述根据预设配置规则对各个拣选工作站配置虚拟槽口的数量，包括：
    确定当前时间和预设时间之间的时间差，所述预设时间根据所述工作站的拣选人员的下线时间确定；
    根据所述时间差和所述拣选人员的工作效率，对拣选人员对应的工作站 配置第三数量的虚拟槽口；所述拣选人员的工作效率为所述拣选人员在单位时间内能够拣选的货物数量；
    其中，所述第三数量为所述拣选人员在所述时间差范围内能够拣选的货物数量对应待处理订单的数量。
  15. 根据权利要求14所述的方法，其特征在于，所述根据所述时间差和所述拣选人员的工作效率，对所述拣选人员对应的工作站配置第三数量的虚拟槽口，包括：
    将时间差和所述拣选人员的工作效率的乘积，对应的待处理订单的数量，确定为对拣选人员对应的工作站配置的虚拟槽口的数量。
  16. 一种订单分配装置，其特征在于，包括：
    获取模块，用于获取多个待处理订单；
    所述获取模块，还用于获取各个拣选工作站的虚拟槽口的数量；其中，每个拣选工作站的虚拟槽口的数量是根据预设配置规则配置的，用于指示该拣选工作站能够处理的待处理订单的数量；
    分配模块，用于根据对各个拣选工作站配置的虚拟槽口的数量，将所述多个待处理订单分配至各个拣选工作站。
  17. 一种计算机设备，其特征在于，包括：
    处理器、存储器及收发器；
    所述存储器存储计算机执行指令；
    所述处理器执行所述存储器存储的计算机执行指令，使得所述处理器执行权利要求1-15任一项所述的方法。
  18. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质中存储有计算机执行指令，所述计算机执行指令被处理器执行时用于实现如上述权利要求1-15任一项所述的方法。
  19. 一种计算机程序产品，包括计算机程序，其特征在于，所述计算机程序被处理器执行时用于实现如权利要求1-15任一项所述的方法。
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