CN119204595B

CN119204595B - Order processing method, device, equipment and storage medium

Info

Publication number: CN119204595B
Application number: CN202411688224.6A
Authority: CN
Inventors: 路光明; 韩明祥; 王辉; 苏权
Original assignee: Hangzhou Hikrobot Co Ltd
Current assignee: Hangzhou Hikrobot Co Ltd
Priority date: 2024-11-22
Filing date: 2024-11-22
Publication date: 2025-03-21
Anticipated expiration: 2044-11-22
Also published as: CN119204595A

Abstract

The application discloses an order processing method, an order processing device, order processing equipment and a storage medium, which relate to the technical field of intelligent storage and are at least used for reasonably processing orders so as to improve carrying efficiency while meeting order timeliness requirements. The method comprises the steps of obtaining order information of a plurality of to-be-processed orders and task information of in-process orders, determining critical processing time of the to-be-processed orders based on the order information of the to-be-processed orders and the number of current handling tasks, determining priority orders of the to-be-processed orders based on the critical processing time of the to-be-processed orders, processing the to-be-processed orders according to the priority orders, wherein the priority of a first order is higher than that of a second order, the priority of the first order is determined based on the order of the critical processing time, and the priority of the second order is determined based on the matching degree of corresponding materials and task residual materials.

Description

Order processing method, device, equipment and storage medium

Technical Field

The present application relates to the field of intelligent warehousing technologies, and in particular, to an order processing method, an order processing device, an order processing apparatus, and a storage medium.

Background

Currently, online shopping has been rapidly developed. The orders generated by shopping on the user line can be automatically carried out by robots in the operator warehouse, and the like, so that the quick delivery and distribution of the materials involved in the orders are realized.

And, in order to satisfy the time-dependent demand of the user for the order, the operator can process the order according to the time of pushing the order to the warehouse. However, since the materials in the warehouse are generally classified and stored in different areas, such a processing manner that preferably satisfies timeliness may cause a problem that it is difficult for the robot to reasonably carry the materials back and forth in the warehouse, resulting in lower carrying efficiency.

Disclosure of Invention

The embodiment of the application provides an order processing method, an order processing device, order processing equipment and a storage medium, which are used for reasonably processing orders so as to improve material handling efficiency while meeting order timeliness requirements.

In order to achieve the above purpose, the embodiment of the present application provides the following technical solutions:

In a first aspect, an order processing method is provided, which includes obtaining order information of a plurality of pending orders, and task information of the pending orders. The order information is used for indicating materials corresponding to the order to be processed and expected delivery time. The task information includes the number of current handling tasks and task remainder. The current handling task is for handling containers storing materials corresponding to an in-process order. And the task residual materials are materials except materials corresponding to the order in the process, wherein the materials stored in the container for carrying the current carrying task are removed. And determining the critical processing time of each of the plurality of pending orders based on the order information of each of the plurality of pending orders and the number of current handling tasks. The critical processing time is the starting processing time when the probability of the order to be processed completing the shipment before the expected shipment time is suddenly reduced from large. The later the start processing time of the pending order, the less probable. And determining the priority order of the plurality of pending orders based on the critical processing time of each of the plurality of pending orders, so as to process the plurality of pending orders according to the priority order. Orders of the first type having a critical processing time no later than the current time have a higher priority than orders of the second type having a critical processing time later than the current time. The priority of the first type of order is based on a sequencing of critical processing times. The priority of the second class of orders is determined based on the matching degree of the corresponding materials and the rest materials of the task.

In the technical scheme, the computer equipment can accurately determine the critical processing time of each of the plurality of orders to be processed. Furthermore, the computer equipment can reasonably determine the priority order of the to-be-processed order based on the critical processing time of the to-be-processed order so as to process the order according to the priority order, so that the to-be-processed order is taken out of the warehouse by combining the task residual materials of the current carrying task on the premise of meeting the timeliness requirement of the to-be-processed order, and the problem that the robot is difficult to reasonably carry the materials back and forth in the warehouse is avoided. Therefore, the application can be used for reasonably processing orders so as to improve the material handling efficiency while meeting the time-efficiency requirement of the orders.

In one possible embodiment, the method for processing the plurality of pending orders according to the priority order specifically comprises the step of distributing the available materials to the highest priority order if the available materials matched with the materials corresponding to the highest priority order exist in the rest materials of the tasks. The order with the highest priority is the order to be processed with the highest priority in the priority order. And if the available materials matched with the materials corresponding to the order with the highest priority do not exist in the rest materials of the tasks, configuring a new carrying task corresponding to the order with the highest priority.

In one possible embodiment, the method for determining the critical processing time of each of the plurality of pending orders based on the order information of each of the plurality of pending orders and the number of current handling tasks specifically includes determining the number of new handling tasks corresponding to the pending orders based on the materials corresponding to the pending orders. The new handling task is used for handling the container storing the material corresponding to the order to be processed. And determining the critical processing time of the order to be processed according to the expected ex-warehouse time of the order to be processed, the number of new carrying tasks and the number of current carrying tasks. The critical processing time is equal to the expected shipment time minus the expected handling time. The estimated duration of the movement is the quotient of the total number of tasks divided by the preset number of tasks. The total number of tasks is the sum of the number of new handling tasks and the number of current handling tasks. The preset number of tasks is used to represent the number of transport tasks allowed to be performed simultaneously per unit time.

In one possible embodiment, the degree of matching of the corresponding material to the task remaining material includes at least one of a ratio between a quantity of material of the matching material and a total quantity of material of the corresponding material, a ratio between a quantity of type of the matching material and a total quantity of type of the corresponding material. The matched materials are materials matched with the rest materials of the task in the corresponding materials.

In one possible embodiment, before acquiring the order information of each of the plurality of pending orders and the task information of the in-process order, the method further includes determining a preset number of orders meeting preset conditions from the plurality of newly added orders, and determining the number of orders to be the plurality of pending orders. The preset order quantity is used for representing the quantity of orders allowed to be processed simultaneously in unit time. The preset conditions comprise at least one of the expected delivery time being earlier than other newly added orders and the material type correlation of the materials corresponding to the to-be-processed orders being greater than or equal to a preset correlation threshold.

In one possible embodiment, the method further comprises sending to the idle workstation, in response to an order acquisition request from the idle workstation, the pending order with the highest priority in the order of priority. The idle work stations are work stations with the number of the pending orders smaller than the number of the preset orders. The preset order quantity is used for representing the quantity of orders allowed to be processed simultaneously in unit time.

In one possible embodiment, the method further comprises determining that the designated order is highest in priority order in response to the processing indication of the designated order.

In a second aspect, an order processing device is provided, comprising an acquisition unit and a processing unit.

The acquisition unit is used for acquiring order information of each of the plurality of pending orders and task information of the pending orders. The order information is used for indicating materials corresponding to the order to be processed and expected delivery time. The task information includes the number of current handling tasks and task remainder. The current handling task is for handling containers storing materials corresponding to an in-process order. And the task residual materials are materials except materials corresponding to the order in the process, wherein the materials stored in the container for carrying the current carrying task are removed.

And the processing unit is used for determining the critical processing time of each of the plurality of to-be-processed orders based on the order information of each of the plurality of to-be-processed orders and the number of the current handling tasks. The critical processing time is the starting processing time when the probability of the order to be processed completing the shipment before the expected shipment time is suddenly reduced from large. The later the start processing time of the pending order, the less probable.

The processing unit is further used for determining the priority order of the plurality of pending orders based on the critical processing time of each of the plurality of pending orders so as to process the plurality of pending orders according to the priority order. Orders of the first type having a critical processing time no later than the current time have a higher priority than orders of the second type having a critical processing time later than the current time. The priority of the first type of order is based on a sequencing of critical processing times. The priority of the second class of orders is determined based on the matching degree of the corresponding materials and the rest materials of the task.

In a possible embodiment, the processing unit is specifically configured to allocate the available material to the highest priority order if there is available material in the remaining materials of the task that matches the material corresponding to the highest priority order. The order with the highest priority is the order to be processed with the highest priority in the priority order. And if the available materials matched with the materials corresponding to the order with the highest priority do not exist in the rest materials of the tasks, configuring a new carrying task corresponding to the order with the highest priority.

In a possible embodiment, the processing unit is specifically configured to determine, based on the material corresponding to the order to be processed, a number of new handling tasks corresponding to the order to be processed. The new handling task is used for handling the container storing the material corresponding to the order to be processed. And determining the critical processing time of the order to be processed according to the expected ex-warehouse time of the order to be processed, the number of new carrying tasks and the number of current carrying tasks. The critical processing time is equal to the expected shipment time minus the expected handling time. The estimated duration of the movement is the quotient of the total number of tasks divided by the preset number of tasks. The total number of tasks is the sum of the number of new handling tasks and the number of current handling tasks. The preset number of tasks is used to represent the number of transport tasks allowed to be performed simultaneously per unit time.

In a possible embodiment, the processing unit is further configured to determine, from the plurality of newly added orders, a preset number of orders that meet a preset condition, and the preset number of orders are a plurality of pending orders. The preset order quantity is used for representing the quantity of orders allowed to be processed simultaneously in unit time. The preset conditions comprise at least one of the expected delivery time being earlier than other newly added orders and the material type correlation of the materials corresponding to the to-be-processed orders being greater than or equal to a preset correlation threshold.

In a possible embodiment the order processing device further comprises a transmitting unit. And the sending unit is used for responding to the order acquisition request from the idle work station and sending the pending order with the highest priority in the priority order to the idle work station. The idle work stations are work stations with the number of the pending orders smaller than the number of the preset orders. The preset order quantity is used for representing the quantity of orders allowed to be processed simultaneously in unit time.

In a possible embodiment, the processing unit is further configured to determine that the priority of the specified order is highest in the priority order in response to a processing indication of the specified order.

In a third aspect, a computer device is provided that includes a processor and a memory. The processor is connected to the memory, the memory is configured to store computer-executable instructions, and the processor executes the computer-executable instructions stored in the memory, thereby implementing any one of the methods provided in the first aspect.

In a fourth aspect, there is provided a readable storage medium comprising computer-executable instructions which, when run on a computer device, cause the computer device to perform any one of the methods provided in the first aspect.

In a fifth aspect, there is provided a computer program product comprising computer-executable instructions which, when run on a computer device, cause the computer device to perform any one of the methods provided in the first aspect.

Technical effects caused by any implementation manner of the second aspect to the fifth aspect may be referred to technical effects caused by corresponding implementation manners of the first aspect, and are not described herein.

Drawings

FIG. 1 is a schematic diagram of an order placement process according to an embodiment of the present application;

fig. 2 is a schematic structural diagram of a computer device according to an embodiment of the present application;

FIG. 3 is a schematic flow chart of an order processing method according to an embodiment of the present application;

FIG. 4 is a schematic illustration of a container according to an embodiment of the present application;

FIG. 5 is a flowchart illustrating another order processing method according to an embodiment of the present application;

Fig. 6 is a schematic structural diagram of an order processing device according to an embodiment of the present application.

Detailed Description

In the description of the present application, "/" means "or" unless otherwise indicated, for example, A/B may mean A or B. The term "and/or" herein is merely an association relation describing the association object, and means that three kinds of relations may exist, for example, a and/or B may mean that a exists alone, a and B exist together, and B exists alone. Furthermore, "at least one" means one or more, and "a plurality" means two or more. The terms "first," "second," and the like do not limit the number and order of execution, and the terms "first," "second," and the like do not necessarily differ.

In the present application, the words "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.

First, in order to facilitate understanding of the present application, relevant elements to which the present application relates will now be described.

The goods-to-person system is a warehouse service system in which a robot carries containers (or shelves, etc.) to a workstation to perform operations such as warehouse-out, warehouse-in, inventory, and tally. The container is used for storing one or more materials.

A workstation is a collection of devices within a work area in a warehouse, including a workstation, computer equipment, code scanning equipment, and the like.

The cut-off time is the time that an order generated by shopping on the subscriber line is pushed to the goods-to-people system. The cut-off time is added to a fixed time, i.e., equal to the latest completed delivery time allowed by the order (or called the expected delivery time). The fixed time can be flexibly set according to the needs.

A wave-order is a collection of orders generated by shopping on a user line.

The timeliness requirement is that the desired order is completed before the allowed latest completed delivery time, i.e. the delivery is completed before the desired delivery time.

The delivery and carrying task is to carry the containers stored with the materials in the warehouse to a workstation for picking according to the material requirements of the orders in the goods-to-people system, so as to complete the delivery and carrying task.

Real-time orders are orders that indicate that the warehouse time and the time of push to the goods-to-people system are within the same time window. For example, an order for a shipment needs to be completed on the day of pushing to the goods-to-people system.

The material property is the type (or class) of material required for an order. For example, if an order requires type A material and type B material, then type A and type B are the material properties of the order.

The task remaining materials are materials which can be distributed after the materials in the container conveyed by the delivery conveying task are distributed to the corresponding order, namely the materials in the conveyed container minus the materials required by the corresponding order.

Exemplary, as shown in fig. 1, a schematic diagram of an order placement process according to an embodiment of the present application is provided. The complete process of an order from pushing to a goods-to-people system to picking the order out of the warehouse via a workstation is shown in fig. 1. Orders generated by shopping on the customer line (real time orders) may be pushed to the total pending order pool of the goods-to-people system first. The total pending order pool may include newly generated orders for the current time window (e.g., the current day) as well as unprocessed orders prior to the current time window.

Orders processed by a workstation are placed from a pool of orders to be processed by the workstation, respectively. For example, orders processed by workstation 1 are placed from a pool of orders to be processed by workstation 1, orders processed by workstation 2 are placed from a pool of orders to be processed by workstation 2, orders processed by workstation 3 are placed from a pool of orders to be processed by workstation 3.

The number of orders that a single workstation supports simultaneous processing may be set to P1. When the number of orders in the pending order pool of any workstation plus the number of orders in the current time processing of the workstation is less than 'P1+1', the any workstation can send an order request to the total pending order pool to trigger order placement. In this way, the total pending order pool may place orders to all of the workstation pending order pools to supplement the number of orders in each workstation pending order pool to the upper limit P2. When the upper limit P2 of the quantity of the orders in the to-be-processed order pool of the workstation is reasonably set to be a smaller value, the efficiency and stability of the processing procedure of the orders of the workstation can be improved.

Optionally, a workstation pending order pool is provided in the goods-to-people system in order to relieve the computing pressure of the processor or the like corresponding to the total pending order pool. With the lifting of computing power of hardware equipment such as a processor and the like or the optimization of an algorithm, the setting of a to-be-processed order pool of a workstation can be canceled. In other words, the total pending order pool may directly generate the out-of-stock transfer tasks for the orders and directly issue the out-of-stock transfer tasks for the orders to the workstation.

Secondly, the application scene related to the application is briefly introduced.

Currently, online shopping has been rapidly developed. Has become a major way of shopping. The orders generated by shopping on the user line can be automatically carried out by robots in the operator warehouse, and the like, so that the quick delivery and distribution of the materials involved in the orders are realized.

With the continuous improvement of the service level and the timeliness of order distribution in the online shopping process of users, it is important to complete order performance timely and accurately with low cost and high efficiency.

Under the goods-to-person system, orders with the same material attribute can be combined into the same wave number and sent to a workstation for delivery. Because two or more orders with the same material attribute can be delivered by carrying the container once, the delivery carrying task which needs to be carried out by the robot can be reduced, thereby reducing equipment investment and improving the delivery efficiency of the orders. But this way ignores the time-consuming demands of the order. The timeliness requirements for orders that are combined together for shipment may be different, easily resulting in a higher timeliness requirement for order lag processing.

In order to meet the timeliness requirement of orders, the orders can be grouped according to the time of cutting the orders, the number of the orders which are supported to be processed in unit time of a workstation and the difference value of the time of cutting the orders among different orders are controlled, so that the orders with earlier time of cutting the orders are executed preferentially, and the timeliness requirement of the orders is met. However, this approach does not take into account the combination of orders with the same material properties, and does not reduce the ex-warehouse handling tasks that need to be performed by the robot, which can easily result in the need to put more equipment into order delivery efficiency.

Next, an implementation environment (implementation architecture) according to the present application will be briefly described.

The embodiment of the application provides an order processing method which can be applied to computer equipment. The computer device may be provided with order processing functionality for maintaining a pool of total pending orders as shown in fig. 1. For example, the computer device may receive real-time orders and place orders to workstations, etc. The embodiments of the present application are not limited in any way to the specific form of the computer device. For example, the computer device may be a terminal device having an order processing function, or may be a network device provided with an order processing function. The terminal device may be referred to as a terminal, user Equipment (UE), a terminal device, a mobile device, a user terminal, a user agent, a user device, or the like. The terminal device may be a mobile phone, a tablet computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, a Personal Digital Assistant (PDA), or the like. The network device may be a server or the like in particular. The server may be one physical or logical server, or may be two or more physical or logical servers sharing different responsibilities, and cooperate to implement various functions of the server.

In hardware implementation, the above-described computer device may be implemented by a computer device as shown in fig. 2. Fig. 2 is a schematic structural diagram of a computer device 10 according to an embodiment of the present application. The computer device 10 may be used to implement the functionality of the computer device described above.

The computer device 10 shown in fig. 2 may include a processor 101, a memory 102, a communication interface 103, and a bus 104. The processor 101, the memory 102, and the communication interface 103 may be connected via a bus 104.

The processor 101 is a control center of the computer device 10, and may be a general-purpose central processing unit (central processing unit, CPU), or may be another general-purpose processor. Wherein the general purpose processor may be a microprocessor or any conventional processor or the like.

As an example, the processor 101 may include one or more CPUs, such as CPU 0 and CPU 1 shown in fig. 2.

Memory 102 may be, but is not limited to, a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (random access memory, RAM) or other type of dynamic storage device that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), magnetic disk storage or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.

In one possible implementation, the memory 102 may exist independently of the processor 101. The memory 102 may be coupled to the processor 101 through the bus 104 for storing data, instructions, or program code. The order processing method provided by the embodiment of the present application can be implemented when the processor 101 calls and executes the instructions or program codes stored in the memory 102.

In another possible implementation, the memory 102 may also be integrated with the processor 101.

A communication interface 103 for connecting the computer device 10 with other devices via a communication network, which may be an ethernet, a radio access network (radio access network, RAN), a wireless local area network (wireless local area networks, WLAN), etc. The communication interface 103 may include a receiving unit for receiving data and a transmitting unit for transmitting data.

Bus 104 may be an industry standard architecture (industry standard architecture, ISA) bus, an external device interconnect (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus, or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in fig. 2, but not only one bus or one type of bus.

It should be noted that the structure shown in fig. 2 does not constitute a limitation of the computer device 10, and that the computer device 10 may include more or less components than shown in fig. 2, or may combine certain components, or may be arranged in different components.

For easy understanding, the order processing method provided by the application is specifically described below with reference to the accompanying drawings.

Fig. 3 is a schematic flow chart of an order processing method according to the present application. The method includes S301-S303.

S301, acquiring order information of each of a plurality of pending orders and task information of the pending orders.

The order information is used for indicating materials corresponding to the order to be processed and expected warehouse-out time.

The order to be processed may be an order in which the material is not placed to a workstation for delivery. For example, in an actual scenario such as e-commerce or new retail, an order may be generated when a user makes an online purchase. The order may include information such as the type and quantity of each material purchased by the user on-line. After the order is generated, the order can be pushed to computer equipment of an operator goods-to-person system such as electronic commerce or new retail for recording. In this manner, the computer device may record the order. And if the materials included in the order are not sent to the workstation for delivery, the order can be considered to be the order to be processed.

The expected time to be out refers to the latest time to complete out that meets the timeliness requirements of the pending order. The expected time to leave the warehouse for different pending orders may be different or the same. Specifically, since the time-efficient demand of different users for order delivery is different, or the receiving address is different, or the logistics carrier is different, the expected delivery time of orders with the same time may be different, and the expected delivery time of orders with different time may be the same. The time of the order is recorded by pushing the order to the computer equipment of the goods-to-person system. For example, the expected time to pick up an order with a later time may be earlier than the expected time to pick up an order with an earlier time.

Alternatively, the desired delivery time may be accurate to minutes, accurate to seconds, etc. For example, the expected time to leave the warehouse may be 14 points for 10 minutes. As another example, the desired time to leave the warehouse may be 14 points 30 minutes 59 seconds.

The material corresponding to the order to be processed may have one or more material types. The number of materials for each material type may be one or more.

The task information for the in-process order may include the number of current handling tasks and task remaining materials. The current handling task is for handling containers storing materials corresponding to an in-process order. That is, the materials in the warehouse are typically stored in containers. A robot typically carries one or more containers while performing a carrying task. It should be understood that the container may alternatively be described as a bin, a containment box, etc., without limitation.

The current handling task may be used to handle the material corresponding to the order currently in process out of the warehouse. The in-process order, i.e., the order that the workstation is processing at the current time. The current transfer task may be a task in which the robot is transferring the container to the workstation, or a task in which the robot has transferred the container to the workstation. That is, the current handling task may be a task of handling the container or a task of picking and discharging the material in the container at the workstation.

And the task residual materials are materials except materials corresponding to the order in the process, wherein the materials stored in the container for carrying the current carrying task are removed. Illustratively, as shown in fig. 4, a schematic diagram of a container according to an embodiment of the present application is provided. Assume that the materials in the container carried by the current carrying task are 9 pieces of materials of type A, and the materials corresponding to the order in the process are 6 pieces of materials of type A. The task remaining material is 3 pieces of type a material after the material in the container being handled by the current handling task has removed the material required for the order in the current process.

S302, determining the critical processing time of each of the plurality of pending orders based on the order information of each of the plurality of pending orders and the number of current handling tasks.

The processing starting time of the order to be processed is the time for starting to process the order to be processed. The later the start processing time of the pending order, the less likely the pending order will complete a shipment before the desired shipment time. The critical processing time is the starting processing time when the probability of the order to be processed completing the shipment before the expected shipment time is suddenly reduced from large. In other words, in the case where the start processing time of the order to be processed is not later than the critical processing time, there is a high probability that the order to be processed can be completed to be taken out before the desired take-out time. In the case where the start processing time of the order to be processed is after the critical processing time, the probability that the order to be processed completes the shipment before the desired shipment time is small.

In one possible approach, the computer may subtract the estimated time from the expected time of the shipment of the order to be processed to obtain a critical processing time for the order to be processed. The estimated time period may be a product of the number of current handling tasks and a preset time period.

Or the computer can determine the number of new carrying tasks corresponding to the order to be processed based on the materials corresponding to the order to be processed, and determine the critical processing time of the order to be processed according to the expected ex-warehouse time of the order to be processed, the number of new carrying tasks and the number of current carrying tasks. The critical processing time is equal to the expected shipment time minus the expected handling time. The estimated duration of the movement is the quotient of the total number of tasks divided by the preset number of tasks. The total number of tasks is the sum of the number of new handling tasks and the number of current handling tasks. The preset number of tasks is used to represent the number of transport tasks allowed to be performed simultaneously per unit time.

S303, determining the priority order of the plurality of pending orders based on the critical processing time of each of the plurality of pending orders, so as to process the plurality of pending orders according to the priority order.

Wherein, the pending orders with critical processing time not later than the current time can be regarded as the first type of orders. Pending orders with critical processing times later than the current time may be considered as second class orders. Orders of the first type are of higher priority than orders of the second type. The priority of each order of the first type is determined based on the order of the critical processing time. The priority of each second class order is determined based on the matching degree of the corresponding material and the rest materials of the task.

In other words, in the case where the critical processing time of one pending order is before or the same as the current time, it may be indicated that the one pending order needs to be processed as soon as possible to meet the timeliness requirement of the one pending order as much as possible. Under the condition that the critical processing time of one to-be-processed order is after the current time, the condition that the time-dependent requirement of the one to-be-processed order is met can be indicated that the residual processing time of the one to-be-processed order is more, and the configuration task residual materials can be preferentially considered for the one to-be-processed order, so that the number of carrying tasks required to be executed by a robot is reduced, and the carrying efficiency is improved.

In one possible manner, the matching degree of the corresponding material and the task residual material comprises at least one of the ratio of the material quantity of the matching material to the total material quantity of the corresponding material, and the ratio of the type quantity of the matching material to the total type quantity of the corresponding material. The matched materials are materials matched with the rest materials of the task in the corresponding materials.

For example, assume that the material corresponding to order 1 includes 5 pieces of type A material. If the task remaining materials of one current handling task are 5 pieces of materials of the type A, the computer equipment can determine that all materials corresponding to the order 1 are met by the task remaining materials, and the matching degree of the task remaining materials and the task remaining materials is calculated to be 1 according to the quantity of the materials. If the task remaining materials of the current handling task are 4 pieces of materials of the type A, the computer equipment can determine that the material part corresponding to the order 1 is met by the task remaining materials, and the matching degree with the task remaining materials is calculated to be 0.8 according to the material quantity. As another example, assume that the material corresponding to order 2 includes 5 pieces of material of type a and 1 piece of material of type B. If the task remaining materials of one current handling task are 5 pieces of materials of type A, the computer equipment can determine that the material part corresponding to the order 2 is met by the task remaining materials, and the matching degree with the task remaining materials is calculated to be 0.5 according to the type number.

If the matching degree of the materials corresponding to the order to be processed and the task residual materials is higher, the fact that the task residual materials of the current carrying task can be used for efficiently completing the ex-warehouse processing of the order can be indicated. If the matching degree of the material corresponding to the order to be processed and the task remaining material is low, the fact that a new carrying task is needed to finish the ex-warehouse processing of the order can be indicated. Therefore, the computer equipment can determine that the second type orders with higher matching degree have higher priority than the second type orders with lower matching degree, so that the utilization rate of materials is improved, the new carrying tasks are reduced as much as possible, and the efficiency of the carrying tasks is improved.

Based on this, the computer device can accurately determine the critical processing time for each of the plurality of pending orders. Furthermore, the computer equipment can reasonably determine the priority order of the to-be-processed order based on the critical processing time of the to-be-processed order, so that the order is distributed to the workstation according to the priority order, and the to-be-processed order is taken out of the warehouse by combining the task residual materials of the current carrying task on the premise of meeting the timeliness requirement of the to-be-processed order, so that the problem that the robot is difficult to reasonably carry the materials back and forth in the warehouse is avoided. Therefore, the application can be used for reasonably processing orders so as to improve the material handling efficiency while meeting the time-efficiency requirement of the orders.

In one embodiment, when processing a plurality of pending orders in a priority order, an embodiment of the present application provides an alternative implementation, including S401-S402.

And S401, if available materials matched with the materials corresponding to the order with the highest priority exist in the rest materials of the task, distributing the available materials to the order with the highest priority.

The order with the highest priority is the order to be processed with the highest priority in the priority order. It should be appreciated that the highest priority order may be either a first type of order or a second type of order.

If the available materials matched with the materials corresponding to the orders with the highest priority exist in the task residual materials, the available materials in the task residual materials can be distributed to the orders with the highest priority. In this case, if all the materials corresponding to the highest priority order are satisfied by the part of available materials, no new transporting task is needed. If the material part corresponding to the order with the highest priority is met by the part of available materials, a conveying task can be added to convey the part which is not met in the material corresponding to the order with the highest priority out of the warehouse. Therefore, part of materials in the residual materials of the task can be utilized, the utilization rate of the materials can be improved, the newly added carrying task can be reduced as much as possible, and the efficiency of the carrying task is improved.

And S402, if the available materials matched with the materials corresponding to the order with the highest priority do not exist in the rest materials of the task, configuring a new carrying task corresponding to the order with the highest priority.

If the available materials matched with the materials corresponding to the order with the highest priority do not exist in the rest materials of the tasks, the computer equipment can configure a new carrying task corresponding to the order with the highest priority so as to carry all the materials corresponding to the order with the highest priority out of the warehouse in a mode of adding the carrying task.

In one embodiment, in determining a critical processing time for each of a plurality of pending orders based on order information for each of the plurality of pending orders and a number of current handling tasks, an embodiment of the present application provides an alternative implementation, including S3021-S3022.

S3021, determining the number of new carrying tasks corresponding to the order to be processed based on the materials corresponding to the order to be processed.

The new handling task is used for handling the container storing the material corresponding to the order to be processed.

In a possible manner, when the computer device determines the number of new handling tasks corresponding to the order to be processed based on the materials corresponding to the order to be processed, the computer device may count all types of materials corresponding to the order to be processed and the number of each type of materials in all types, so as to obtain the number of various types of materials required by the order to be processed. And, the computer device may determine the number of new handling tasks corresponding to each type of material as the quotient of the number of each type of material divided by the preset container capacity. Furthermore, the computer device may add the number of new handling tasks corresponding to each type of material in the total types to obtain the number of new handling tasks corresponding to the order to be processed.

For example, assume that the types of materials corresponding to the order to be processed are two types of A type and B type, the number of materials of the A type is 20 pieces, the number of materials of the B type is 20 pieces, and the preset container capacity is 10 pieces. The computer device may determine the number of new handling tasks corresponding to type a materials as quotient 2 of the number of type a materials 20 divided by the preset container capacity 10. Meanwhile, the computer equipment can determine the number of new carrying tasks corresponding to the type B materials as quotient 2 obtained by dividing the number of the type B materials by 10 preset container capacity. Furthermore, the computer device may add the number of new handling tasks corresponding to the type a material and the number of new handling tasks corresponding to the type B material, to obtain the number of new handling tasks corresponding to the order to be processed as 4.

Or when the computer equipment determines the number of new handling tasks corresponding to the to-be-processed order based on the materials corresponding to the to-be-processed order, the number of new handling tasks can be determined according to the number of the materials of various types required by the to-be-processed order and the material stock information after counting the number of the materials of various types required by the to-be-processed order. Wherein the stock information may include the amount of each type of material in stock stored in the respective container. In particular, the computer device may combine the individual containers storing each type of material based on the amount of each type of material required for the order to be processed and determine a corresponding target combination for each type of material. The sum of the storage numbers of the containers in the target combination corresponding to each type of material is greater than or equal to the number of each type of material required for the order to be processed. And, among the various combinations corresponding to each type of material, the number of containers in the target combination is minimized.

In this manner, the computer device may determine the number of containers in the target combination for each type of material as the number of new handling tasks for each type of material. Furthermore, the computer device may add the number of new handling tasks corresponding to each type of material in the total types to obtain the number of new handling tasks corresponding to the order to be processed.

By way of example, assume that the types of materials corresponding to the order to be processed are two types a and B, and the number of materials of type a is 21 pieces, the number of materials of type B is 7 pieces, and the number of materials of type a stored in the container 1 is 5 pieces, the number of materials stored in the container 2 is 8 pieces, the number of materials stored in the container 3 is 10 pieces, and the number of materials of type B stored in the container 4 is 2 pieces, and the number of materials stored in the container 5 is 9 pieces in the material inventory information. The computer device may determine that the target combination 1 for type a materials includes container 1, container 2, and container 3, and that the target combination 2 for type b materials includes container 5.

In this way, the computer device may determine that the number of new handling tasks corresponding to the type a material is 3 of the containers in the target set 1, and the number of new handling tasks corresponding to the type b material is 1 of the containers in the target set 2. Furthermore, the computer device may add the number of new handling tasks 3 corresponding to the type a material to the number of new handling tasks 1 corresponding to the type B material, to obtain the number of new handling tasks corresponding to the target wavelength as 4.

S3022, determining the critical processing time of the order to be processed according to the expected ex-warehouse time of the order to be processed, the number of new carrying tasks and the number of current carrying tasks.

Wherein the critical processing time is equal to the expected shipment time minus the expected handling time. The estimated duration of the movement is the quotient of the total number of tasks divided by the preset number of tasks. The total number of tasks is the sum of the number of new handling tasks and the number of current handling tasks. The preset number of tasks is used to represent the number of transport tasks allowed to be performed simultaneously per unit time.

In a possible manner, when the computer device determines the critical processing time of the order to be processed according to the expected delivery time of the order to be processed, the number of current handling tasks and the number of new handling tasks may be added and divided by the preset number of tasks to obtain the estimated handling time, and then the estimated handling time is subtracted from the expected delivery time to obtain the critical processing time. For example, assuming that the preset number of tasks is TS1, the current number of transfer tasks is TS2, the new number of transfer tasks is TS3, and the desired delivery time is T1, the critical process time t2=t1- (ts2+ts3)/TS 1.

Or when the computer equipment determines the critical processing time of the order to be processed according to the expected delivery time of the order to be processed, the number of new delivery tasks and the number of current delivery tasks, the quotient of the number of the current delivery tasks divided by the number of preset tasks is multiplied by the preset weight, and then the quotient of the number of the new delivery tasks divided by the number of the preset tasks is added to obtain the estimated delivery time, and then the estimated delivery time is subtracted from the expected delivery time to obtain the critical processing time. The preset weight can be flexibly set based on the estimated execution progress of the current carrying task. The quotient of the number of the current handling tasks divided by the number of the preset tasks can be regarded as the handling duration corresponding to the current handling tasks. Considering that the current carrying task may have been executed for a certain period of time, the period of time actually required for completing the current carrying task can be estimated more accurately after the carrying period of time corresponding to the current carrying task is multiplied by the preset weight, and further the estimated carrying period of time can be obtained more accurately.

In one embodiment, before acquiring order information of each of a plurality of pending orders and task information of an in-process order, the order processing method provided by the embodiment of the application further includes S501.

S501, determining the number of orders meeting preset conditions from a plurality of newly added orders, wherein the number of the orders meets the preset conditions and is a plurality of pending orders.

The preset order quantity is used for representing the quantity of orders allowed to be processed simultaneously in unit time. The preset conditions comprise at least one of the expected delivery time being earlier than other newly added orders and the material type correlation of the materials corresponding to the to-be-processed orders being greater than or equal to a preset correlation threshold.

It should be appreciated that the newly added order may be an order that is newly pushed to the goods-to-people system of an operator such as an e-commerce or new retail.

Multiple pending orders may also be considered orders for one wave. In other words, the computer device may group the plurality of newly added orders to process the orders by the number of orders.

In one possible manner, the number of the plurality of pending orders may be less than or equal to the preset order number. The preset number of orders may be used to represent the number of orders that a single workstation supports simultaneous processing. Therefore, under the condition that a plurality of orders to be processed are distributed to the workstation as one wave number to be processed, the workstation can process the plurality of orders to be processed simultaneously, and the problem that part of orders need to be processed due to the fact that the number of the orders is large is avoided, so that order processing efficiency is improved.

Under the condition that the expected delivery time is earlier than other newly added orders, the computer equipment can determine a plurality of pending orders according to the expected delivery time of each of the plurality of newly added orders. In this case, the closer the expected time to leave the order to be processed is relative to the current time, the greater the probability of being determined as the order to be processed.

For example, the computer device may sort the plurality of pending orders in a sequence of the desired delivery times from first to second, resulting in a sequence of pending orders. Furthermore, the computer device may select a preset number of orders to be processed from the sequence of orders to be processed in order from front to back, so as to obtain a plurality of orders to be processed.

For another example, the computer device sets respective corresponding priority weights for the plurality of pending orders according to the expected delivery time corresponding to the pending orders and the duration of the current time interval. When the expected time of delivery is longer than the duration of the current time interval, the priority weight corresponding to the order to be processed is larger. The smaller the expected time of delivery and the duration of the current time interval, the smaller the priority weight corresponding to the order to be processed. Furthermore, the computer device may select, from the plurality of pending orders, a preset number of pending orders with a higher priority according to the order of the priority from the higher priority to the lower priority, to obtain a plurality of pending orders.

In the case that the preset condition includes that the material type correlation with the material corresponding to the order to be processed is greater than or equal to the preset correlation threshold, the material type correlation among the plurality of orders to be processed may be greater than or equal to the preset correlation threshold. The preset correlation threshold can be flexibly set according to actual needs.

For example, the computer device may determine a material type correlation between the newly added order and the order to be processed according to whether the material corresponding to the newly added order includes a material of a preset type. If the material corresponding to the newly added order comprises a material of a preset type, the computer equipment can determine that the material type correlation degree between the newly added order and the order to be processed is 1. If the material corresponding to the newly added order does not comprise the material of the preset type, the computer equipment can determine that the material type correlation degree between the newly added order and the order to be processed is 0.

For another example, the computer device may also determine a correlation of a material type between the newly added order and the order to be processed according to a cosine similarity of a material type between a material corresponding to the newly added order and a material corresponding to the order to be processed. Specifically, a material type may be mapped to a vector. Thus, for the material type of the material corresponding to one newly added order, the computer device can map the material type corresponding to the newly added order into a set of vectors. Furthermore, the computer equipment can determine cosine similarity of the material types between the material corresponding to the newly added order and the material corresponding to the order to be processed.

For another example, the computer device may also determine a material type correlation between the newly added order and the order to be processed by determining whether the material corresponding to the newly added order and the material corresponding to the order to be processed are stored in the same container. It is assumed that type a materials and type B materials are stored in the same container. If order 3 requires a type of material and order 4 requires a type of material, the computer device may determine that the materials corresponding to order 3 and order 4 are stored in the same container, and determine that the material type correlation between order 3 and order 4 is 1. If order 3 requires a type of material and a type of material, and order 4 requires a type of material, the computer device may determine that the materials corresponding to order 3 and order 4 are stored in the same container, and determine that the material type correlation between order 3 and order 4 is 1.

Therefore, the correlation degree of the material types among the plurality of to-be-processed orders can be larger than or equal to the preset correlation degree threshold, and the workstation can more easily combine the carrying tasks among the plurality of to-be-processed orders under the condition that the plurality of to-be-processed orders are distributed to the workstation for processing, so that the carrying tasks which are required to be executed by a robot are reduced, and the order processing efficiency is improved.

Under the condition that the expected delivery time is earlier than other newly-increased orders and the material type correlation degree of the materials corresponding to the to-be-processed orders is greater than or equal to a preset correlation degree threshold value, the computer equipment can screen the newly-increased orders with the shorter expected delivery time interval current time from the newly-increased orders according to the respective expected delivery time of the newly-increased orders. And under the condition of screening a plurality of newly added orders with a short current time interval when the expected warehouse-out is carried out, the computer equipment can further screen the newly added orders with the material type correlation degree of the corresponding materials larger than or equal to a preset correlation degree threshold value from the newly added orders to obtain a plurality of pending orders.

In one possible embodiment, the processing of the pending order may be triggered by an idle workstation. In this case, the order processing method provided by the embodiment of the application further comprises S601.

And S601, responding to an order acquisition request from the idle workstation, and sending the pending order with the highest priority in the priority order to the idle workstation.

The idle work stations are work stations with the quantity of the to-be-processed orders smaller than the quantity of the preset orders. The preset order quantity is used for representing the quantity of orders allowed to be processed simultaneously in unit time.

In one implementation, the idle workstation may send an order acquisition request to the computer device for acquiring the pending order if the number of allocated orders is less than the preset number of orders. Accordingly, the computer device may receive an order acquisition request from the idle workstation. In this case, the computer device may determine the priority order of the respective pending orders in response to the order acquisition request, and send the pending order with the highest priority among the priority orders to the idle workstation.

In a possible manner, in the case that the order to be processed with the highest priority is the first order, the computer device may send the instruction information to the idle workstation while sending the order to be processed with the highest priority in the priority order to the idle workstation. The indication information can be used for indicating that a transport task which is independently used for processing the to-be-processed order is newly added. Therefore, the idle workstation can receive the waiting order with the highest priority and the indication information, newly add the carrying task which is used for processing the waiting order according to the indication information, and preferentially execute the newly added carrying task so as to rapidly process the waiting order, thereby meeting the timeliness requirement of the waiting order.

In one possible embodiment, the computer device may periodically determine the order of priority of the plurality of pending orders so as to efficiently and reasonably respond to the order acquisition requests of the idle workstations, effectively meeting the timeliness requirements of the orders. Specifically, the computer device may periodically obtain the number of current handling tasks in each workstation and periodically determine the critical processing time for each of the plurality of pending orders. Further, the computer device may periodically determine a time-to-time relationship between the critical processing time and the current time to further determine a priority order of the plurality of pending orders.

In one possible embodiment, the staff member may instruct immediate out-of-stock processing of the designated order. In this case, the order processing method provided by the embodiment of the application further comprises S701.

S701, in response to a processing instruction of the designated order, determining that the designated order has the highest priority in the priority order.

In one implementation, a worker may send a processing indication specifying an order to a computer device via a headend device. In this case, the computer device may determine that the designated order has the highest priority in the priority order in response to the processing instruction of the designated order. As such, the computer device may prioritize the designated orders to meet the order processing requirements.

In one embodiment, as shown in fig. 5, a flow chart of another order processing method provided by the present application is shown. The order processing method shown in fig. 5 includes S801 to S809.

S801, triggering to place an order to an idle workstation when the idle workstation exists.

Alternatively, the computer device may determine that an idle workstation exists upon receiving a request message from a workstation for acquiring a pending order. Or the computer device may determine that there are idle workstations in the event that it is determined that there are workstations for which the number of allocated orders is less than the preset number of orders.

S802, acquiring order information of each of a plurality of pending orders and task information of the pending orders.

S803, determining respective critical processing time of the plurality of pending orders based on respective order information of the plurality of pending orders and the number of current handling tasks.

S804, determining whether a first order with critical processing time not later than the current time exists.

If there is a first type order with critical processing time not later than the current time, then S805 is performed.

If there is no first type order with critical processing time not later than the current time, then S806 is performed.

S805, sending a first order to the idle workstation.

S806, acquiring task residual materials corresponding to the current carrying task.

And S807, if materials matched with the materials corresponding to the second type of orders with the critical processing time later than the current time exist in the task residual materials, distributing the matched materials to the second type of orders.

S808, if the materials matched with the materials corresponding to the second class of orders do not exist in the rest materials of the task, determining a plurality of target orders from the second class of orders according to preset conditions, and configuring a new carrying task corresponding to the plurality of target orders.

It should be understood that the implementation of S808 may refer to the descriptions related to S501 and S3021, which are not described herein.

S809, sending a plurality of target orders to the idle workstation.

In one implementation manner, after the execution of S809, the idle workstation may add one or more transfer tasks to process an order in which a portion of the corresponding material is satisfied by the task remaining material of the current transfer task, or to process an order in which all of the material is not satisfied by the task remaining material. In this case, the newly added one or more handling tasks may be regarded as the current handling task, and the remaining materials of the corresponding tasks may be used for being combined with other orders to be allocated to other orders, so as to reduce the number of handling tasks and improve the efficiency of the handling tasks.

It should be appreciated that the computer device may cycle through the processes described above in S801-S809 until all orders are completed for shipment.

The foregoing description of the embodiments of the present application has been presented primarily in terms of methods. It will be appreciated that the computer device, in order to carry out the functions described above, includes at least one of a corresponding hardware structure and software module for performing the respective functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

The embodiment of the application can divide the functional units of the computer equipment according to the method example, for example, each functional unit can be divided corresponding to each function, and two or more functions can be integrated in one processing unit. The integrated units may be implemented in hardware or in software functional units. It should be noted that, in the embodiment of the present application, the division of the units is schematic, which is merely a logic function division, and other division manners may be implemented in actual practice.

By way of example, fig. 6 shows a schematic diagram of an order processing device. The order processing device 20 may be adapted to perform the methods referred to in the above embodiments. The order processing apparatus 20 includes an acquisition unit 901 and a processing unit 902.

The acquiring unit 901 is configured to acquire order information of each of a plurality of pending orders, and task information of an in-process order. The order information is used for indicating materials corresponding to the order to be processed and expected delivery time. The task information includes the number of current handling tasks and task remainder. The current handling task is for handling containers storing materials corresponding to an in-process order. And the task residual materials are materials except materials corresponding to the order in the process, wherein the materials stored in the container for carrying the current carrying task are removed.

The processing unit 902 is configured to determine a critical processing time of each of the plurality of pending orders based on order information of each of the plurality of pending orders and a number of current handling tasks. The critical processing time is the starting processing time when the probability of the order to be processed completing the shipment before the expected shipment time is suddenly reduced from large. The later the start processing time of the pending order, the less probable.

The processing unit 902 is further configured to determine a priority order of the plurality of pending orders based on the critical processing time of each of the plurality of pending orders, so as to process the plurality of pending orders according to the priority order. Orders of the first type having a critical processing time no later than the current time have a higher priority than orders of the second type having a critical processing time later than the current time. The priority of the first type of order is based on a sequencing of critical processing times. The priority of the second class of orders is determined based on the matching degree of the corresponding materials and the rest materials of the task.

In one possible embodiment, the processing unit 902 is specifically configured to assign the available material to the highest priority order if there is an available material in the remaining materials of the task that matches the material corresponding to the highest priority order. The order with the highest priority is the order to be processed with the highest priority in the priority order. And if the available materials matched with the materials corresponding to the order with the highest priority do not exist in the rest materials of the tasks, configuring a new carrying task corresponding to the order with the highest priority.

In a possible embodiment, the processing unit 902 is specifically configured to determine, based on the material corresponding to the order to be processed, a number of new handling tasks corresponding to the order to be processed. The new handling task is used for handling the container storing the material corresponding to the order to be processed. And determining the critical processing time of the order to be processed according to the expected ex-warehouse time of the order to be processed, the number of new carrying tasks and the number of current carrying tasks. The critical processing time is equal to the expected shipment time minus the expected handling time. The estimated duration of the movement is the quotient of the total number of tasks divided by the preset number of tasks. The total number of tasks is the sum of the number of new handling tasks and the number of current handling tasks. The preset number of tasks is used to represent the number of transport tasks allowed to be performed simultaneously per unit time.

In a possible embodiment, the processing unit 902 is further configured to determine, from the multiple newly added orders, a preset number of orders that meet a preset condition, where the preset number of orders is multiple pending orders. The preset order quantity is used for representing the quantity of orders allowed to be processed simultaneously in unit time. The preset conditions comprise at least one of the expected delivery time being earlier than other newly added orders and the material type correlation of the materials corresponding to the to-be-processed orders being greater than or equal to a preset correlation threshold.

In a possible embodiment, the order processing device 20 further comprises a sending unit 903. A sending unit 903, configured to send, to the idle workstation, a pending order with the highest priority in the priority order in response to an order acquisition request from the idle workstation. The idle work stations are work stations with the number of the pending orders smaller than the number of the preset orders. The preset order quantity is used for representing the quantity of orders allowed to be processed simultaneously in unit time.

In a possible embodiment, the processing unit 902 is further configured to determine, in response to a processing indication of the specified order, that the specified order has a highest priority in the priority order.

For a specific description of the above alternative modes, reference may be made to the foregoing method embodiments, and details are not repeated here. In addition, any explanation of the computer device and description of the beneficial effects provided above may refer to the corresponding method embodiments described above, and are not repeated.

As an example, in connection with fig. 2, some or all of the functions in the acquisition unit 901, the processing unit 902, and the transmission unit 903 in the order processing apparatus 20 may be realized by the processor 101 in fig. 2 executing the program code in the memory 102 in fig. 2.

Embodiments of the present application also provide a computer readable storage medium having stored thereon a computer program which, when run on a computer, causes the computer to perform a method performed by any of the computer devices provided above.

For the explanation of the relevant content and the description of the beneficial effects in any of the above-mentioned computer-readable storage media, reference may be made to the above-mentioned corresponding embodiments, and the description thereof will not be repeated here.

Embodiments of the present application also provide a computer program product comprising instructions which, when run on a computer, cause the computer to perform any of the methods of the above embodiments. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions in accordance with embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, a website, computer, server, or data center via a wired (e.g., coaxial cable, fiber optic, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. Computer readable storage media can be any available media that can be accessed by a computer or data storage devices including one or more servers, data centers, etc. that can be integrated with the media. Usable media may be magnetic media (e.g., floppy disks, hard disks, magnetic tape), optical media (e.g., DVD), etc.

It should be noted that the above-mentioned devices for storing computer instructions or computer programs, such as, but not limited to, the above-mentioned memories, computer-readable storage media, etc., provided by the embodiments of the present application all have non-volatile (non-transmission).

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using a software program, it may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions in accordance with embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, a website, computer, server, or data center via a wired (e.g., coaxial cable, fiber optic, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. Computer readable storage media can be any available media that can be accessed by a computer or data storage devices including one or more servers, data centers, etc. that can be integrated with the media. Usable media may be magnetic media (e.g., floppy disks, hard disks, magnetic tape), optical media (e.g., DVD), etc.

Although the application is described herein in connection with various embodiments, other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed application, from a study of the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

Although the application has been described in connection with specific features and embodiments thereof, it will be apparent that various modifications and combinations can be made without departing from the spirit and scope of the application. Accordingly, the specification and drawings are merely exemplary illustrations of the present application as defined in the appended claims and are considered to cover any and all modifications, variations, combinations, or equivalents that fall within the scope of the application. It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

Claims

1. An order processing method, comprising:

The method comprises the steps of obtaining order information of each of a plurality of to-be-processed orders and task information of in-process orders, wherein the order information is used for indicating materials corresponding to the to-be-processed orders and expected ex-warehouse time, the task information comprises the number of current handling tasks and task residual materials, the current handling tasks are used for handling containers storing the materials corresponding to the in-process orders, and the task residual materials are materials except the materials corresponding to the in-process orders, wherein the materials are stored in the handling containers of the current handling tasks;

Determining respective critical processing time of the plurality of to-be-processed orders based on order information of the plurality of to-be-processed orders and the number of current carrying tasks, wherein the critical processing time is starting processing time when the probability of the to-be-processed orders completing the ex-warehouse before the expected ex-warehouse time is suddenly reduced, the probability is smaller when the starting processing time of the to-be-processed orders is later, the critical processing time is equal to the expected ex-warehouse time minus the expected carrying time, the expected carrying time is a quotient of the number of new carrying tasks and the number of current carrying tasks after being added and divided by the number of preset tasks, the number of the new carrying tasks is determined based on materials corresponding to the to-be-processed orders, and the number of the preset tasks is used for representing the number of carrying tasks allowed to be simultaneously executed in unit time;

Determining the priority order of the multiple orders to be processed based on the critical processing time of each of the multiple orders to be processed, so as to process the multiple orders to be processed according to the priority order, wherein the priority of a first order with critical processing time not later than the current time is higher than a second order with critical processing time later than the current time, the priority of the first order is determined based on the order of the critical processing time, and the priority of the second order is determined based on the matching degree of the corresponding materials and the rest materials of the task.

2. The method of claim 1, wherein said processing said plurality of pending orders in said order of priority comprises:

If the available materials matched with the materials corresponding to the order with the highest priority exist in the rest materials of the task, distributing the available materials to the order with the highest priority, wherein the order with the highest priority is the order to be processed with the highest priority in the priority order;

And if the available materials matched with the materials corresponding to the orders with the highest priority are not present in the task residual materials, configuring a new carrying task corresponding to the order with the highest priority.

3. The method of claim 1, wherein the degree of matching of the corresponding material to the task remaining material comprises at least one of a ratio of a quantity of material of the matching material to a total quantity of material of the corresponding material, a ratio of a type quantity of the matching material to a total type quantity of material of the corresponding material, and a matching material of the corresponding material to the task remaining material.

4. A method according to any one of claims 1-3, wherein prior to obtaining order information for each of the plurality of pending orders and task information for the in-process order, the method further comprises:

the method comprises the steps of determining the number of the preset orders from a plurality of newly added orders, wherein the number of the preset orders is used for representing the number of the orders allowed to be processed simultaneously in unit time, and the preset conditions comprise at least one of the expected ex-warehouse time is earlier than other newly added orders, and the material type correlation degree of materials corresponding to the to-be-processed orders is larger than or equal to a preset correlation degree threshold value.

5. The method according to claim 1, wherein the method further comprises:

And responding to an order acquisition request from an idle work station, and sending the order to be processed with the highest priority in the priority sequence to the idle work station, wherein the idle work station is a work station with the number of the orders to be processed being smaller than the number of preset orders, and the preset order number is used for representing the number of the orders allowed to be processed simultaneously in unit time.

6. The method according to claim 1, wherein the method further comprises:

in response to a processing indication of a designated order, determining that the designated order has a highest priority in the priority order.

7. An order processing device is characterized by comprising an acquisition unit and a processing unit;

The system comprises an acquisition unit, a task information processing unit and a task processing unit, wherein the acquisition unit is used for acquiring order information of each of a plurality of to-be-processed orders and task information of in-process orders, the order information is used for indicating materials corresponding to the to-be-processed orders and expected ex-warehouse time, the task information comprises the number of current handling tasks and task residual materials, the current handling tasks are used for handling containers storing the materials corresponding to the in-process orders, and the task residual materials are materials except the materials corresponding to the in-process orders, which are stored in the handling containers of the current handling tasks;

The processing unit is used for determining respective critical processing time of the plurality of to-be-processed orders based on order information of the plurality of to-be-processed orders and the number of current carrying tasks, wherein the critical processing time is starting processing time when the probability of the to-be-processed orders completing the delivery before the expected delivery time is suddenly reduced from large, the probability of the to-be-processed orders being smaller when the starting processing time is later, the critical processing time is equal to the expected delivery time minus the expected carrying time, the expected carrying time is the quotient of the number of new carrying tasks and the number of current carrying tasks added and divided by the number of preset tasks, the number of the new carrying tasks is determined based on materials corresponding to the to-be-processed orders, and the number of preset tasks is used for representing the number of carrying tasks allowed to be simultaneously executed in unit time;

the processing unit is further used for determining the priority order of the plurality of orders to be processed based on the critical processing time of each of the plurality of orders to be processed, so that the plurality of orders to be processed are processed according to the priority order, the priority of a first order with critical processing time not later than the current time is higher than a second order with critical processing time later than the current time, the priority of the first order is determined based on the priority of the critical processing time, and the priority of the second order is determined based on the matching degree of the corresponding materials and the rest materials of the task.

8. A computer device, comprising: a processor;

the processor is connected to a memory for storing computer-executable instructions that the processor executes to cause the computer device to implement the method of any one of claims 1-6.

9. A readable storage medium storing computer instructions which, when run on a computer device, cause the computer device to perform the method of any one of claims 1-6.