Order scheduling method, device and equipment and computer readable storage medium

Abstract

The application provides an order production scheduling method and device, equipment and a computer readable storage medium. The method comprises the following steps: receiving a request message for production scheduling, the request message carrying a warehouse to be scheduled, a time to be scheduled and a site to be scheduled; obtaining backlog order information of each backlog order in a backlog order set, warehouse information of each warehouse in a warehouse set and site information of each site in a site set; determining a target production scheduling plan based on the backlog order information, the warehouse information and the site information, the target production scheduling plan being a target order to be produced from the warehouse to be scheduled to the site to be scheduled at the time to be scheduled; and sending the target production scheduling plan to a terminal in a response message, so that the terminal schedules the target order according to the target production scheduling plan. The backlog order is optimized and scheduled based on the backlog order information, the warehouse information and the site information to determine the target production scheduling plan, backlog orders can be quickly produced, the number of backlog orders is reduced, and the scheduling efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of warehouse management technology, and includes, but is not limited to, an order scheduling method, apparatus, equipment, and computer-readable storage medium. Background Technology

[0002] With the development of internet technology, more and more users are choosing to shop online. During the ordering and delivery process, various circumstances may cause logistics and courier services to suspend operations, leading to order backlogs at warehouses and delivery stations, sometimes reaching tens of millions of orders. Given the limited capacity of warehouses and delivery stations, determining the daily order volume to be produced by each region and warehouse for each station, in order to fully utilize limited warehouse and station capacity, produce as many backlogged orders as possible, and process them as quickly as possible, has become a pressing issue. Summary of the Invention

[0003] In view of this, embodiments of this application provide an order scheduling method, apparatus, device, and computer-readable storage medium.

[0004] The technical solution of this application embodiment is implemented as follows:

[0005] This application provides an order scheduling method, the method including:

[0006] Receive a request message for production scheduling, the request message carrying the warehouse to be scheduled, the time to be scheduled, and the site to be scheduled;

[0007] Retrieve backlog order information for each backlog order in the backlog order set, warehouse information for each warehouse in the warehouse set, and site information for each site in the site set;

[0008] Based on the backlog order information, warehouse information, and site information, a target production schedule is determined. The target production schedule is the target orders that the warehouse to be scheduled will pre-produce to the site to be scheduled during the scheduled production time.

[0009] The target production schedule is sent to the terminal in a response message so that the terminal can schedule the target order according to the target production schedule.

[0010] In some embodiments, obtaining the backlog order information of each backlog order in the backlog order set, the warehouse information of each warehouse in the warehouse set, and the site information of each site in the site set includes:

[0011] Obtain the order identifier, order time, production warehouse location, production warehouse, and delivery station for each backlogged order in the backlogged order set; determine the order identifier, order time, production warehouse location, production warehouse, and delivery station for each backlogged order as the backlogged order information for each backlogged order;

[0012] Obtain the warehouse capacity and location of each warehouse in the warehouse centralization; determine the warehouse capacity and location of each warehouse as the warehouse information of each warehouse;

[0013] Obtain the available site capacity, target delivery volume, and location of each site in the site set; determine the available site capacity, target delivery volume, and location of each site as the site information of each site.

[0014] In some embodiments, obtaining the available site capacity of each site in the site set includes:

[0015] Obtain the in-transit order information of each in-transit order in the in-transit order set. The in-transit order is an order that has been produced but has not yet been successfully delivered to the corresponding station. The in-transit order information includes the in-transit order identifier, order placement time, production warehouse location, production warehouse, expected delivery station, and expected delivery time.

[0016] Based on the pre-delivery stations of each in-transit order, determine the pre-occupied station capacity of each station;

[0017] Based on the target delivery volume of each site in the site cluster and the pre-occupied site capacity, the available site capacity of each site in the site cluster is determined.

[0018] In some embodiments, determining the target production schedule based on the backlog order information, warehouse information, and site information includes:

[0019] Obtain the distance between each region and the production site to be scheduled;

[0020] Based on the distance between each region and the production site to be scheduled, the regions are sorted to obtain the region sorting result;

[0021] Based on the location of the production warehouse for each backlog of orders, determine the production target volume for different regions;

[0022] Based on the backlog of orders, warehouse capacity, available site capacity, regional sorting results, and production target, a target production schedule is determined.

[0023] In some embodiments, determining the target production schedule based on the backlog order information, warehouse capacity, available site capacity, regional sorting results, and production target includes:

[0024] Based on the order identifier of each backlogged order, obtain the backlogged order quantity;

[0025] Based on the warehouses awaiting production, the time of production waiting, the sites awaiting production, the backlog of orders, the warehouse capacity, the available site capacity, and the production target, a dynamic decision-making model is constructed.

[0026] Based on the dynamic decision-making model, the target production schedule is determined.

[0027] In some embodiments, the step of constructing a dynamic decision-making model based on the pending production warehouse, pending production time, pending production site, backlog of orders, warehouse capacity, available site capacity, and production target includes:

[0028] Decision constraints are determined based on the backlog of orders, warehouse capacity, available site capacity, and production target.

[0029] Based on the warehouses, production times, and production sites to be scheduled, the decision-making objectives are determined.

[0030] A dynamic decision-making model is constructed based on the decision constraints and the decision objective.

[0031] In some embodiments, the method further includes:

[0032] Based on the target production schedule, determine the remaining site capacity of each site and the remaining warehouse capacity of each warehouse;

[0033] Based on the remaining capacity of each site, the capacity of each site is adjusted to obtain the adjusted site capacity.

[0034] Based on the remaining warehouse capacity of each warehouse, the warehouse capacity of each warehouse is adjusted to obtain the adjusted warehouse capacity.

[0035] This application embodiment provides an order scheduling device, the device comprising:

[0036] The receiving module is used to receive a request message for production scheduling, the request message carrying the warehouse to be scheduled, the time to be scheduled, and the site to be scheduled;

[0037] The acquisition module is used to acquire backlog order information for each backlog order in the backlog order set, warehouse information for each warehouse in the warehouse set, and site information for each site in the site set.

[0038] The first determining module is used to determine a target production schedule based on the backlog order information, warehouse information and site information. The target production schedule is the target orders that the warehouse to be scheduled will pre-produce to the site to be scheduled during the scheduled production time.

[0039] The sending module is used to send the target production schedule in a response message to the terminal so that the terminal can schedule the target order according to the target production schedule.

[0040] This application provides an electronic device, including:

[0041] Processor; and

[0042] Memory for storing computer programs that can run on the processor;

[0043] The computer program, when executed by the processor, implements the steps of the above-mentioned order scheduling method.

[0044] This application provides a computer-readable storage medium storing computer-executable instructions configured to perform the steps of the above-described order scheduling method.

[0045] This application provides an order scheduling method, apparatus, device, and computer-readable storage medium. The method includes: receiving a scheduling request message, the request message carrying a warehouse to be scheduled, a scheduling time, and a scheduling site; acquiring backlog order information for each backlog order in a backlog order set, warehouse information for each warehouse in a warehouse set, and site information for each site in a site set; determining a target scheduling plan based on the backlog order information, warehouse information, and site information, the target scheduling plan being a target order to be pre-produced by the warehouse to be scheduled to the scheduling site at the scheduled time; and sending the target scheduling plan in a response message to a terminal, so that the terminal schedules the target order according to the target scheduling plan. The order scheduling method provided in this application optimizes the scheduling of backlog orders based on backlog order information, warehouse information, and site information, determines the target order to be pre-produced by the warehouse to be scheduled to the scheduling site at the scheduled time, coordinates the capacity of the scheduling sites, and can quickly produce backlog orders, reduce the amount of backlog orders, and improve scheduling efficiency. Attached Figure Description

[0046] In the accompanying drawings (which are not necessarily drawn to scale), similar reference numerals may describe similar parts in different views. The drawings illustrate, by way of example and not limitation, the various embodiments discussed herein.

[0047] Figure 1 This is a schematic diagram of the network architecture of the order scheduling system provided in the embodiments of this application;

[0048] Figure 2 This is a schematic diagram illustrating an implementation process of the order scheduling method provided in an embodiment of this application.

[0049] Figure 3 This is a schematic diagram illustrating one implementation process of the step of obtaining the available site capacity of each site in the site set in the method provided in the embodiments of this application;

[0050] Figure 4 This is a schematic diagram illustrating an implementation process of the step of determining the target production schedule in the method provided in the embodiments of this application;

[0051] Figure 5 A schematic diagram illustrating another implementation flow of the order scheduling method provided in this application embodiment;

[0052] Figure 6 This is a schematic diagram of the composition structure of the order scheduling and layout optimization system provided in the embodiments of this application;

[0053] Figure 7 A schematic diagram of the decision-making process provided in the embodiments of this application;

[0054] Figure 8 A schematic diagram of the composition structure of an order scheduling device provided in an embodiment of this application;

[0055] Figure 9 This is a schematic diagram of the composition structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0057] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0058] In the following description, the terms "first, second, third" are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0060] Before providing a more detailed description of the embodiments of this application, we will first explain the defects existing in the order scheduling schemes of related technologies.

[0061] In related technologies, when faced with a large backlog of orders that need to be produced, issues such as limited warehouse capacity, limited site capacity, the need to coordinate the use of site capacity between regions, and different time differences between production in different warehouses and arrival at the sites are mainly addressed by manual solutions: based on feedback from regional operating sites and their capacity, the total production target value for each region is determined manually, and then the production target value for each warehouse is determined based on the total production target value for each region. Based on the operating sites and their capacity, orders for production in each warehouse are then pulled down. The solutions in the relevant technologies have the following drawbacks: 1) Since each region and warehouse is based on the same operating site and site capacity data when placing production orders, there is insufficient communication and coordination between regions, resulting in some sites not fully utilizing their capacity and some sites having more pending orders than their capacity; 2) The time difference between the production time of orders from different regions and their arrival at the site is not carefully considered. Typically, local warehouses produce orders on the same day and deliver them to the site on the same day, remote warehouses produce orders on the same day and deliver them to the site the next day, and even more remote warehouses produce orders on the same day and deliver them to the site more than a few days later; 3) There is a certain degree of flexibility in setting site capacity and warehouse capacity. Currently, due to the inability to locate the bottlenecks in site capacity and warehouse capacity, the flexibility in capacity cannot be fully utilized.

[0062] To address the aforementioned problems, embodiments of this application provide an order scheduling method and apparatus. The method provided by these embodiments will be described below in conjunction with the apparatus used to implement them. First, the order scheduling system provided by these embodiments will be described. See [link to documentation]. Figure 1 , Figure 1 This is a schematic diagram of the network architecture of the order scheduling system provided in the embodiments of this application, such as... Figure 1 As shown, the order scheduling system 10 includes at least one terminal device 100, a service device 200, and a network 300. The terminal device 100 is connected to the service device 200 through the network 300, which can be a wide area network, a local area network, or a combination of both, and uses a wireless link to achieve data transmission.

[0063] In some embodiments, the terminal device 100 may be a laptop, tablet, desktop computer, smartphone, dedicated messaging device, portable gaming device, smart speaker, smartwatch, or other interactive device. The service device 200 may be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server. The network 300 may be a wide area network (WAN), a local area network (LAN), or a combination of both. The terminal device 100 and the service device 200 may be directly or indirectly connected via wired or wireless communication, which is not limited in this embodiment.

[0064] In the application scenario of this order scheduling system architecture, when the terminal device 100 receives a trigger command based on user operation, it generates a request message for scheduling. This request message carries the warehouse to be scheduled, the time to be scheduled, and the site to be scheduled. The terminal device 100 then sends this request message to the service device 200.

[0065] Service device 200 receives a request message for production scheduling, parses the request message to obtain the warehouse to be scheduled, the time to be scheduled, and the site to be scheduled; it obtains the backlog order information of each backlog order in the backlog order set, the warehouse information of each warehouse in the warehouse set, and the site information of each site in the site set; based on the backlog order information, warehouse information, and site information, it determines the target production scheduling plan, which is the target order to be pre-produced by the warehouse to be scheduled to the site to be scheduled at the time to be scheduled; finally, it sends the target production scheduling plan to the terminal device 100 in a response message.

[0066] After receiving the response message sent by the service device 200, the terminal device 100 parses it to obtain the target production schedule and schedules the target order according to the target production schedule.

[0067] The order scheduling method provided in this application optimizes the scheduling of backlogged orders based on backlogged order information, warehouse information, and site information to determine the target scheduling plan. This method can quickly produce backlogged orders, reduce the amount of backlogged orders, and improve scheduling efficiency.

[0068] The following describes the order scheduling method provided in the embodiments of this application. In some embodiments, the order scheduling method provided in the embodiments of this application can be provided by... Figure 1 The service equipment implementation of the network architecture shown. Figure 2 This is a schematic diagram illustrating an implementation process of the order scheduling method provided in this application embodiment, which will be combined with... Figure 2 The steps shown are explained.

[0069] Step S201: Receive a request message for production scheduling.

[0070] This embodiment of the application can be executed by an order scheduling device in a service device. When a user needs to produce backlogged orders, a user operation for scheduling is performed on a terminal device. The terminal device responds to the user operation, triggers a scheduling instruction, and generates a request message based on this instruction. This request message carries the warehouse to be scheduled, the scheduling time, and the scheduling site. The terminal device sends the generated request message to the service device. After receiving the request message from the terminal device, the order scheduling device of the service device parses it to obtain the warehouse to be scheduled, the scheduling time, and the scheduling site carried in the request message.

[0071] Step S202: Obtain the backlog order information of each backlog order in the backlog order set, the warehouse information of each warehouse in the warehouse set, and the site information of each site in the site set.

[0072] The order scheduling device retrieves a backlog of orders from the database and obtains the order identifier, order time, production warehouse location, production warehouse, and delivery station for each backlogged order. This information is then used to define the backlogged order information for each order. The order identifier is the unique identifier of the order, and the production warehouse for each backlogged order is the warehouse that produced that order. In this embodiment, the production warehouse is divided into zones based on geographical location. Taking Company J as an example, it is assumed to have several zones: HB, HZ, HN, HD, XB, XN, and DB. If the production warehouse is located in City S, then its zone is HD. The delivery station is the station where the order is successfully delivered. The HD, HB, HZ, HN, XB, XN, and DB zones are pre-defined zones based on geographical location.

[0073] The order scheduling device retrieves a warehouse set from the database and obtains the warehouse capacity and location of each warehouse in the warehouse set; it then defines the warehouse capacity and location of each warehouse as its warehouse information. In this embodiment, warehouse capacity refers to the production capacity of a warehouse that can be used to produce backlogged orders, that is, the storage capacity of a warehouse that can be used to store backlogged orders.

[0074] The order scheduling device retrieves a site set from the database and obtains the available site capacity, target delivery volume, and location of each site in the site set. The available site capacity, target delivery volume, and location of each site are then defined as the site information for that site. In this embodiment, the sites in the site set are operational sites; that is, the site set does not include non-operational (closed) sites. Site capacity refers to the total storage capacity of the site, available site capacity is the available storage capacity of the site, and target delivery volume refers to the total number of orders to be delivered to that site. The location of a site refers to which of the following regions—HD, HB, HZ, HN, XB, XN, and DB—the site is located in.

[0075] Step S203: Determine the target production schedule based on backlog order information, warehouse information, and site information.

[0076] Warehouses in different regions have varying delivery times to the same production site, resulting in a time lag. For example, a production site located in City S might have its backlog of orders delivered to it on the same day they are produced by a local warehouse in City S. However, a remote warehouse in City XB might take 2-3 days to deliver the backlog of orders after production begins. Therefore, a target production schedule needs to be determined by considering the location of the production site, the location of the warehouse, and the pre-set delivery times between regions.

[0077] In one implementation, when determining the target production schedule, the order scheduling device first obtains the distance between each region and the production site to be scheduled; based on the distances, the regions are sorted to obtain a region sorting result; then, based on the region where the production warehouse for each backlog of orders is located, the production target quantity for different regions is determined; finally, based on the backlog of orders information, warehouse capacity, available site capacity, region sorting result, and production target quantity, the target production schedule is determined. This target production schedule is the target orders that the production warehouse will pre-produce to the production site during the production waiting period.

[0078] Step S204: The target production schedule is sent to the terminal in the response message so that the terminal can schedule the target order according to the target production schedule.

[0079] The order scheduling device generates a response message based on the target production plan and sends the generated response message to the terminal. After receiving the response message sent by the order scheduling device, the terminal parses it to obtain the target production plan and schedules the target order according to the target production plan.

[0080] The order scheduling method provided in this application embodiment involves an order scheduling device receiving a request message for scheduling, which carries the warehouse to be scheduled, the scheduling time, and the scheduling site; acquiring backlog order information for each backlog order in the backlog order set, warehouse information for each warehouse in the warehouse set, and site information for each site in the site set; determining a target scheduling plan based on the backlog order information, warehouse information, and site information, whereby the target scheduling plan is the pre-production of target orders from the warehouse to the site at the scheduling time; and sending the target scheduling plan in a response message to the terminal, so that the terminal can schedule the target orders according to the target scheduling plan. This method optimizes the scheduling of backlog orders by using backlog order information, warehouse information, and site information to determine the target scheduling plan, enabling rapid production of backlog orders, reducing the backlog order volume, and improving scheduling efficiency.

[0081] In some embodiments, Figure 2 In the illustrated embodiment, "obtaining the available site capacity of each site in the site set" can be achieved through... Figure 3 The following steps are shown to achieve this:

[0082] Step S301: Obtain the transit order information of each transit order in the transit order set.

[0083] Here, "orders in transit" refers to orders that have been produced but not yet delivered to the corresponding site. The information for orders in transit includes the order identifier, order placement time, location of the production warehouse, production warehouse, expected delivery site, and expected delivery time.

[0084] Step S302: Determine the pre-occupied station capacity of each station based on the pre-delivery stations of each in-transit order.

[0085] The total number of all in-transit orders at each pre-delivery station is added together to obtain the pre-allocated station capacity for each station.

[0086] Step S303: Determine the available site capacity of each site in the site cluster based on the target delivery volume and the pre-occupied site capacity of each site in the site cluster.

[0087] The available site capacity of each site in the site cluster is calculated by subtracting the pre-occupied site capacity from the target delivery volume of the site.

[0088] In some embodiments, the above Figure 2 Step S203 in the illustrated embodiment, "Determine the target production schedule based on backlog order information, warehouse information, and site information," can be achieved through... Figure 4 The following steps are shown to achieve this:

[0089] Step S401: Obtain the distance between each region and the production site to be scheduled.

[0090] The location of the production site to be scheduled is fixed. The distance between the production site to be scheduled and a certain area can be the distance between the production site to be scheduled and the center point of the area, which can be the centroid of the area. The distance between the production site to be scheduled and the area can also be the average distance between the production site to be scheduled and the warehouses in the area.

[0091] Step S402: Sort each region according to the distance between each region and the production site to be scheduled, and obtain the region sorting result.

[0092] The smaller the distance between a region and the production site, the earlier orders produced in that region will arrive at the production site; conversely, the greater the distance, the later orders will arrive. Based on this, the estimated arrival time of orders produced in each region can be calculated according to the distance between the region and the production site. This allows for the regions to be ranked, resulting in a region ranking result.

[0093] Taking a production site in City S as an example, orders produced by warehouses in region HD (where City S is located) on day T can be delivered to the production site within T+1 days. Orders produced by warehouses in regions HB, HZ, and HN on day T can be delivered within T+2 days. Orders produced by warehouses in regions XB, XN, and DB on day T can be delivered within T+3 days. Therefore, the ordering result can be ①HD, ②HB, HZ, HN, ③XB, XN, DB. Here, HD, HB, HZ, HN, XB, XN, and DB are regions pre-defined according to geographical location.

[0094] Step S403: Determine the production target volume for different regions based on the location of the production warehouse for each backlog of orders.

[0095] Based on the production warehouses of each backlog of orders, determine the production target for each warehouse, and add up the target production quantities of all warehouses belonging to the same region to obtain the target production quantity for that region.

[0096] Step S404: Determine the target production schedule based on backlog order information, warehouse capacity, available site capacity, regional sorting results, and production target volume.

[0097] To summarize one implementation method and determine the target production schedule, the following steps can be followed:

[0098] Step S4041: Obtain the backlog of orders based on the order identifier of each backlog order.

[0099] Different backlogged orders have different order identifiers. The number of backlogged orders is determined based on the number of order identifiers.

[0100] Step S4042: Construct a dynamic decision-making model based on the warehouse to be scheduled, the time to be scheduled, the site to be scheduled, the backlog of orders, the warehouse capacity, the available site capacity, and the production target.

[0101] The order scheduling device determines the decision constraints based on the backlog of orders, warehouse capacity, available site capacity, and production target: the daily warehouse order scheduling output is not allowed to exceed the daily warehouse capacity; under the constraint of the total regional production volume, the production volume of all warehouses in the region cannot exceed the target production volume; the daily order volume arriving at the site is not allowed to exceed the daily site capacity. Based on these constraints, the constraint condition st is determined as follows (1); based on the warehouse to be scheduled, the scheduling time, and the scheduling site, the decision objective is determined as follows (2); finally, based on the decision constraints and decision objective, a dynamic decision model is constructed.

[0102]

[0103]

[0104] Wherein, the production site to be scheduled is J = {1,…,j}, the region is D = {1,…,d}, and all warehouses I within region d are... d ={1,…,i}, all regional warehouses I = {I d}, the production schedule time T={1,…,t}.

[0105] The backlog of orders from warehouse i∈I to production site j∈J ij ∈Z + The production time t is the warehouse capacity of warehouse i∈I. Production target quantity for the region d∈D during the production scheduling time t Production scheduling time t, production scheduling site j∈J, site capacity The time difference δ between the production scheduling time t and the production time of the backlog of orders in region d∈D d ∈Z + The time difference η between the production scheduling time t and the delivery time of the backlog of orders in region d∈D d ∈Z + .

[0106] Decision variables Z represents the backlog of orders to be produced by warehouse i∈I on day t∈T and sent to production site j∈J. + Represents a positive integer.

[0107] Step S4043: Determine the target production schedule based on the dynamic decision-making model.

[0108] In this embodiment, after constructing the dynamic decision-making model, multiple optimal solutions to the dynamic decision-making model can be sought based on an evolutionary algorithm. These multiple optimal solutions are the production scheduling results corresponding to multiple production sites to be scheduled, thus obtaining the target production schedule. In actual implementation, the evolutionary algorithm can specifically be a genetic evolutionary algorithm.

[0109] Based on the above embodiments, this application further provides an order scheduling method. Figure 5 This is a schematic diagram illustrating another implementation flow of the order scheduling method provided in the embodiments of this application, as follows: Figure 5 As shown, the method includes the following steps:

[0110] Step S501: Receive a request message for production scheduling.

[0111] The request message carries the warehouse to be scheduled, the time to be scheduled, and the site to be scheduled.

[0112] Steps S501 to S504 in the embodiments of this application are respectively related to... Figure 2In the illustrated embodiment, steps S201 to S204 correspond one-to-one. For detailed implementation of steps S501 to S504, please refer to [link to documentation]. Figure 2 Steps S201 to S204 in the illustrated embodiment.

[0113] Step S502: Obtain the backlog order information of each backlog order in the backlog order set, the warehouse information of each warehouse in the warehouse set, and the site information of each site in the site set.

[0114] Step S503: Determine the target production schedule based on backlog order information, warehouse information, and site information.

[0115] The target production schedule here refers to the target orders that will be pre-produced by the waiting-to-be-scheduled warehouse to the waiting-to-be-scheduled site during the waiting-to-be-scheduled production period.

[0116] Step S504: The target production schedule is sent to the terminal in the response message so that the terminal can schedule the target order according to the target production schedule.

[0117] In practical applications, when processing backlogged orders, some sites or warehouses may reach daily order saturation, becoming bottlenecks. These sites and warehouses can be expanded to increase capacity, thus completing the backlog more quickly. Conversely, some sites or warehouses may remain underutilized; these can be scaled down to reduce capacity, potentially saving resources. In practice, the following steps can be used to update site and warehouse capacity.

[0118] Step S505: Based on the target production schedule, determine the remaining site capacity of each site and the remaining warehouse capacity of each warehouse.

[0119] The order scheduling unit first determines the order quantity to be delivered to each site based on the target production schedule. Then, based on the order quantity and capacity of each site, it determines the remaining capacity of each site. Next, based on the target production schedule, it determines the order quantity to be produced in each warehouse. Finally, based on the order quantity produced in each warehouse and its capacity, it determines the remaining warehouse capacity of each warehouse.

[0120] Step S506: Based on the remaining station capacity of each station, adjust the station capacity of each station to obtain the adjusted station capacity.

[0121] Based on the remaining capacity of each site, determine whether it has reached a bottleneck. If it has, expand its capacity and increase the site's capacity; if it has not reached a bottleneck, reduce its capacity and decrease the site's capacity. This is how the adjusted site capacity is obtained.

[0122] Step S507: Based on the remaining warehouse capacity of each warehouse, adjust the warehouse capacity of each warehouse to obtain the adjusted warehouse capacity.

[0123] Based on the remaining warehouse capacity of each warehouse, determine whether it has reached a bottleneck. If it has, expand its capacity and increase its capacity; if it has not reached a bottleneck, reduce its capacity and decrease its capacity. This is how the adjusted warehouse capacity is obtained.

[0124] In this embodiment, after the terminal schedules production for the target order according to the target production plan, the warehouse capacity and site capacity are adjusted according to the saturation level of the site and warehouse. Production is scheduled according to the adjusted site capacity and warehouse capacity, which can avoid excessive surplus capacity in the site or warehouse leading to resource waste. While ensuring optimized production, resources can be saved.

[0125] The following will describe an exemplary application of the embodiments of this application in a real-world application scenario.

[0126] In daily life, various factors can lead to lockdowns in certain areas, resulting in a backlog of logistics and express delivery orders. If the lockdown is prolonged, this can even lead to a backlog of tens of millions of orders. Some of these backlogged orders are produced by local warehouses, while others are produced by warehouses outside the local area. After the lockdown is lifted, warehouses gradually resume operations. Given the limited capacity of warehouses and delivery stations, there is an urgent need to develop an order scheduling and optimization system to determine the daily order volume from each warehouse to each delivery station, in order to fully utilize the limited warehouse and delivery station capacity and produce as many backlogged orders as possible.

[0127] In related technologies, the daily order volume produced by each region and warehouse to each station is mainly estimated manually. The main idea of ​​the manual solution is as follows: based on the feedback of the operating stations and station capacity collected in the region, the headquarters user determines the total production target value of each region. Then, the users in each region determine the production target value of each warehouse based on the total production target value. The users in each warehouse then pull down the production orders based on the operating stations and capacity. In actual operation, this manual solution revealed the following problems: 1) Since each region and warehouse is based on the same operating site and site capacity data when placing production orders, there is insufficient communication and coordination between regions, resulting in some sites not fully utilizing their capacity and some sites having more pending orders than their capacity; 2) It does not take into account the time difference between orders from different regions arriving at the site after production scheduling. Typically, local warehouses produce on the same day and deliver to the site on the second day, nearby warehouses (e.g., XN warehouse, XB warehouse) produce on the same day and deliver to the site on the third day, and distant warehouses (e.g., XN warehouse, XB warehouse) produce on the same day and deliver to the site on the fourth day; 3) There is a certain degree of flexibility in setting site and warehouse capacity. Currently, due to the inability to identify the bottlenecks in site and warehouse capacity, the flexibility cannot be fully utilized.

[0128] In related technologies, order scheduling optimization mainly focuses on optimizing the order scheduling sequence under the actual production process of manufacturing enterprises, and mostly utilizes heuristic methods such as ant colony algorithms and genetic algorithms. This method does not make accurate solutions more efficient when the problem scale is small, and it is not conducive to subsequent sensitivity analysis to guide parameter tuning. Manual rules are currently a commonly used method in actual operations, but when facing multiple areas requiring coordination, it is difficult to provide the optimal strategy from a global perspective.

[0129] This application aims to design an order scheduling optimization system that is practical and executable, balancing the capacity utilization of warehouses and stations in different regions. It primarily addresses the issue of large order backlogs caused by lockdown measures under special circumstances. As warehouses and stations gradually reopen, the system needs to formulate order scheduling plans for each warehouse over a period of time to process backlogged orders as quickly as possible, while ensuring that the production volume does not exceed warehouse capacity and the order volume arriving at each station does not exceed station capacity. This technical solution effectively solves the problems exposed by manual solutions in actual operation: 1) By constructing a multi-stage dynamic decision-making model, it ensures priority production of orders originating from local warehouses and maximizes the utilization of station and regional warehouse capacity; 2) The integer programming model constructed for each stage considers the time difference between regional warehouse capacity utilization and station capacity utilization, with the time difference for different regions derived from operational experience; 3) Analyzing the optimal order scheduling scheme under the current parameter settings can identify warehouses and stations with capacity bottlenecks, guiding how to adjust the capacity of key warehouses and key stations within an adjustable range to maximize the production of backlogged orders. This technical solution conforms to the logic of human decision-making, fully considers the experience accumulated by human solutions, such as the flexible adjustment space of warehouse and site capacity settings, and can make up for the problems exposed by human solutions during operation.

[0130] This application embodiment constructs an order scheduling and layout optimization system with a multi-stage dynamic decision-making model at its core. Figure 6 This is a schematic diagram of the composition structure of the order scheduling and layout optimization system provided in the embodiments of this application, as shown below. Figure 6 As shown, the system mainly consists of five modules: an order input module 61, a delivery target setting module 62, a warehouse capacity constraint setting module 63, a layout optimization scheme output module 64, and a parameter adjustment module 65. Details are as follows:

[0131] 1. Order Input Module 61: This module is used to prepare the data input required by the model, including OFC paused order quantity (i.e. backlog order quantity), in-transit order quantity, etc.

[0132] 1) OFC Suspended Orders: The backlog of orders that have not yet been produced. Data fields include order date, region of the order production warehouse, order production warehouse, and order delivery site.

[0133] 2) Orders in transit: The number of orders that have been produced but not yet delivered. Data fields include the estimated arrival time of the orders at the destination.

[0134] 2. Delivery Target Setting Module 62: Used to determine the delivery target for each station.

[0135] 1) Collect information on the operating sites and their corresponding capacity. The delivery target is the upper limit of the capacity of all sites. The total delivery target equals the sum of the upper limits of the capacity of all sites.

[0136] 2) Achieving the site delivery target includes two parts: the number of orders in transit and the number of backlogged orders. Since orders in transit will occupy site capacity, when analyzing the site capacity available for backlogged orders, it is necessary to subtract the occupied site capacity from the delivery target.

[0137] 3. Warehouse capacity constraint setting module 63: Used to determine the target value of production for each regional warehouse, as well as the capacity of each warehouse.

[0138] 1) Under the logic of the manual solution, the headquarters determines the production target value of each region based on the target value of the site delivery. In order to make the technical solution more in line with the decision-making process of the manual solution and to keep the solution within a controllable range, this logic will continue to be retained in the solution.

[0139] 2) Collect the production capacity of each region and warehouse that can be used to produce backlogged orders.

[0140] IV. Layout Optimization Scheme Output Module 64: Used to determine the order volume produced by each warehouse to each site at each decision time point, and the production plan will be updated daily.

[0141] 1) Multi-stage dynamic decision-making model: At decision time T-1, it is necessary to decide on the order scheduling plan for each warehouse on day T. Considering that the local warehouse can reach the site on day T+1, it can reach the site first compared to the external warehouse. The shorter the link, the more stable it is. Therefore, a multi-stage dynamic decision-making model is adopted to prioritize the production of the local warehouse. If the production of the local warehouse cannot fully utilize the site's capacity, then the production of the external warehouse will be considered. Figure 7 This is a schematic diagram of the multi-stage dynamic decision-making framework provided in the embodiments of this application, such as... Figure 7 As shown, the specific logic is as follows:

[0142] For example, under existing capacity constraints, determine the production plan for warehouse HD (local warehouse) from T to T+3, and the order volume arriving at the station from T+1 to T+4. This order volume will pre-occupy station capacity, therefore the station capacity from T+1 to T+4 needs to be updated. Under the updated capacity constraints, considering that warehouses HN, HZ, and HB can produce on day T and arrive at the station on day T+2, prioritize the arrival of warehouses XN, XB, and DB. Similarly, prioritize determining the production plan for warehouses HN, HZ, and HB from T to T+2, and determine the order volume arriving at the station from T+2 to T+4. This order volume will also pre-occupy station capacity, therefore the station capacity from T+2 to T+4 needs to be updated. Finally, determine the production plan for warehouses XN, XB, and DB from T to T+1, and determine the order volume arriving at the station from T+3 to T+4.

[0143] 2) Integer programming model: used to make decisions on order scheduling plans for each region and warehouse.

[0144] The set of all stations in City S is represented by J = {1, ..., j}, the set of all regions is represented by D = {1, ..., d}, and the set of all warehouses within region d is represented by I. d ={1,…,i}, and the set of all warehouses is represented as I = {I d The set of all decision-making time points is represented as T = {1, ..., t}.

[0145] The number of backlogged orders from warehouse i to station j is represented by o. ij The production capacity of warehouse i from decision time t is represented as: The production target from decision time t to region d is represented as: The capacity from decision time t to station j is represented as: The time difference between the decision-making time point and the production time point of the backlog order warehouse in region d is expressed as δ. d The time difference between the decision-making time and the arrival time of the backlog of orders in region d at the city S station is denoted as η. d .

[0146] The decision variable is the quantity of orders produced by warehouse i and sent to site j at decision time t, denoted as: Based on the above set and parameters, the constraints of the integer programming model can be expressed as equations (3) to (7):

[0147]

[0148]

[0149]

[0150]

[0151]

[0152] Among them, Z + Represents a positive integer.

[0153] Explanation: Constraints (3) and (4) stipulate that the daily warehouse order output cannot exceed the daily warehouse capacity. Constraint (6) stipulates that under the constraint of the total regional target production volume, the production volume of all warehouses in the region cannot exceed the target production volume, so as to avoid the production volume of a certain region being too large and exceeding the maximum value of contract production that the headquarters sets for the region. Constraint (7) limits the number of orders arriving at the station each day to not exceeding the station's daily capacity.

[0154] V. Parameter Adjustment Module 65: Based on the optimal order scheduling and layout optimization scheme, analysis is performed as follows:

[0155] 1) Warehouse capacity utilization: Compare the warehouse capacity with the warehouse capacity occupied by the optimization plan. If the warehouse capacity occupied by the optimization plan is equal to the warehouse capacity, then the warehouse capacity is considered to have reached its bottleneck.

[0156] 2) Site capacity utilization: Compare the site capacity with the site capacity occupied by the optimization plan. If the site capacity occupied by the optimization plan is equal to the site capacity, then the site capacity is considered to have reached its bottleneck.

[0157] 3) If there are warehouses or stations with capacity bottlenecks among the backlog of unproduced orders, these warehouses or stations should be the focus of adjustment when adjusting warehouse and station capacity.

[0158] The method provided in this application addresses several issues when facing a large backlog of orders requiring production. These issues include limited warehouse capacity, limited site capacity, the need to coordinate site capacity usage between regions, and varying time differences between warehouse production and delivery to sites. The multi-stage dynamic decision-making scheme offered by this invention comprehensively solves these problems and prioritizes production in local warehouses while considering the stability of the solution's implementation. This solution quickly provides an optimal warehouse order scheduling plan that coordinates resources from all parties, ensuring feasibility. Furthermore, when collecting warehouse and site capacity data, there is a certain degree of flexibility in setting warehouse and site capacity, allowing for fluctuations within a certain range. This invention provides data analysis to guide the setting of warehouse and site capacity, maximizing the production output of backlogged orders within the operational space.

[0159] Based on the foregoing embodiments, this application provides an order scheduling device. The various modules and units included in the device can be implemented by a processor in a computer device; of course, they can also be implemented by specific logic circuits. In the implementation process, the processor can be a central processing unit (CPU), a microprocessor unit (MPU), a digital signal processor (DSP), or a field programmable gate array (FPG A), etc.

[0160] This application embodiment further provides an order scheduling device. Figure 8 A schematic diagram of the composition structure of the order scheduling device provided in the embodiments of this application is shown below. Figure 8 As shown, the order scheduling device 800 includes:

[0161] The receiving module 801 is used to receive a request message for production scheduling, the request message carrying the warehouse to be scheduled, the time to be scheduled, and the site to be scheduled.

[0162] The acquisition module 802 is used to acquire backlog order information of each backlog order in the backlog order set, warehouse information of each warehouse in the warehouse set, and site information of each site in the site set;

[0163] The first determining module 803 is used to determine a target production schedule based on the backlog order information, warehouse information and site information. The target production schedule is the target orders that the warehouse to be scheduled will pre-produce to the site to be scheduled during the scheduled production time.

[0164] The sending module 804 is used to send the target production schedule in a response message to the terminal so that the terminal can schedule the target order according to the target production schedule.

[0165] In some embodiments, the acquisition module 802 is further configured to:

[0166] Obtain the order identifier, order time, production warehouse location, production warehouse, and delivery station for each backlogged order in the backlogged order set; determine the order identifier, order time, production warehouse location, production warehouse, and delivery station for each backlogged order as the backlogged order information for each backlogged order; obtain the warehouse capacity and location of each warehouse in the warehouse set; determine the warehouse capacity and location of each warehouse as the warehouse information for each warehouse; obtain the available site capacity, target delivery volume, and location of each site in the site set; determine the available site capacity, target delivery volume, and location of each site as the site information for each site.

[0167] In some embodiments, the acquisition module 802 is further configured to:

[0168] Obtain the in-transit order information for each in-transit order in the in-transit order set. The in-transit orders are those that have been produced but not yet successfully delivered to the corresponding stations. The in-transit order information includes the in-transit order identifier, order placement time, location of the production warehouse, production warehouse, expected delivery station, and expected delivery time. Based on the expected delivery stations of each in-transit order, determine the pre-allocated station capacity for each station. Based on the successful delivery target volume of each station in the station set and the pre-allocated station capacity, determine the available station capacity for each station in the station set.

[0169] In some embodiments, the first determining module 803 is further configured to:

[0170] Obtain the distance between the production sites to be scheduled and each region; sort the regions according to the distance to obtain the region sorting result; determine the production target quantity for each region according to the region where the production warehouse of each backlog order is located; determine the target production schedule according to the backlog order information, warehouse capacity, available site capacity, region sorting result and production target quantity.

[0171] In some embodiments, the first determining module 803 is further configured to:

[0172] Based on the order identifier of each backlogged order, obtain the backlogged order quantity; based on the pending production warehouse, pending production time, pending production site, backlogged order quantity, warehouse capacity, available site capacity, and production target quantity, construct a dynamic decision-making model; based on the dynamic decision-making model, determine the target production schedule.

[0173] In some embodiments, the first determining module 803 is further configured to:

[0174] Based on the backlog of orders, warehouse capacity, available site capacity, and production target, decision constraints are determined; based on the warehouses to be scheduled, the scheduling time, and the sites to be scheduled, decision objectives are determined; and based on the decision constraints and the decision objectives, a dynamic decision model is constructed.

[0175] In some embodiments, the apparatus further includes:

[0176] The second determining module is used to determine the remaining site capacity of each site and the remaining warehouse capacity of each warehouse according to the target production schedule.

[0177] The first adjustment module is used to adjust the site capacity of each site based on the remaining site capacity of each site, so as to obtain the adjusted site capacity.

[0178] The second adjustment module is used to adjust the warehouse capacity of each warehouse based on the remaining warehouse capacity of each warehouse, so as to obtain the adjusted warehouse capacity.

[0179] It should be noted that the description of the above-described order scheduling device embodiments is similar to the description of the above-described methods, and has the same beneficial effects as the method embodiments. For technical details not disclosed in the order scheduling device embodiments of this application, those skilled in the art should refer to the description of the method embodiments of this application for understanding.

[0180] It should be noted that, in the embodiments of this application, if the above methods are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this application are not limited to any specific hardware and software combination.

[0181] Accordingly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps in the order scheduling method provided in the above embodiments.

[0182] This application provides an electronic device. Figure 9 This is a schematic diagram of the composition structure of an electronic device provided in an embodiment of this application. Figure 9 The exemplary structure of the electronic device 900 shown can be used to deduce other exemplary structures of the electronic device 900. Therefore, the structure described herein should not be regarded as a limitation. For example, some components described below may be omitted, or components not described below may be added to suit the specific needs of certain applications.

[0183] Figure 9 The illustrated electronic device 900 includes: a processor 901, at least one communication bus 902, a user interface 903, at least one external communication interface 904, and a memory 905. The communication bus 902 is configured to enable communication between these components. The user interface 903 may include a display screen, and the external communication interface 904 may include standard wired and wireless interfaces. The processor 901 is configured to execute a program of an order scheduling method stored in the memory to implement the steps of the order scheduling method provided in the above embodiments.

[0184] The descriptions of the above embodiments of the electronic devices and storage media are similar to those of the above method embodiments, and have similar beneficial effects. For technical details not disclosed in the embodiments of the electronic devices and storage media of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0185] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0186] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0187] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0188] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0189] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0190] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0191] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a device to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0192] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An order scheduling method, characterized in that, The method includes: Receive a request message for production scheduling, the request message carrying the warehouse to be scheduled, the time to be scheduled, and the site to be scheduled; Retrieve backlog order information for each backlog order in the backlog order set, warehouse information for each warehouse in the warehouse set, and site information for each site in the site set; Based on the backlog order information, warehouse information, and site information, a target production schedule is determined. The target production schedule is the target orders that the warehouse to be scheduled will pre-produce to the site to be scheduled during the scheduled production time. The target production schedule is sent to the terminal in a response message so that the terminal can schedule the target order according to the target production schedule. The acquisition of backlog order information for each backlog order in the backlog order set, warehouse information for each warehouse in the warehouse set, and site information for each site in the site set includes: Obtain the order identifier, order time, production warehouse location, production warehouse, and delivery station for each backlogged order in the backlogged order set; determine the order identifier, order time, production warehouse location, production warehouse, and delivery station for each backlogged order as the backlogged order information for each backlogged order; Obtain the warehouse capacity and location of each warehouse in the warehouse centralization; determine the warehouse capacity and location of each warehouse as the warehouse information of each warehouse; Obtain the available site capacity, target delivery volume, and location of each site in the site set; determine the available site capacity, target delivery volume, and location of each site as the site information of each site.

2. The method according to claim 1, characterized in that, The acquisition of available site capacity for each site in the site set includes: Obtain the in-transit order information of each in-transit order in the in-transit order set. The in-transit order is an order that has been produced but has not yet been successfully delivered to the corresponding station. The in-transit order information includes the in-transit order identifier, order placement time, production warehouse location, production warehouse, expected delivery station, and expected delivery time. Based on the pre-delivery stations of each in-transit order, determine the pre-occupied station capacity of each station; Based on the target delivery volume of each site in the site cluster and the pre-occupied site capacity, the available site capacity of each site in the site cluster is determined.

3. The method according to claim 2, characterized in that, The process of determining the target production schedule based on the backlog order information, warehouse information, and site information includes: Obtain the distance between each region and the production site to be scheduled; Based on the distance between each region and the production site to be scheduled, the regions are sorted to obtain the region sorting result; Based on the location of the production warehouse for each backlog of orders, determine the production target volume for different regions; Based on the backlog of orders, warehouse capacity, available site capacity, regional sorting results, and production target, a target production schedule is determined.

4. The method according to claim 3, characterized in that, The step of determining the target production schedule based on the backlog order information, warehouse capacity, available site capacity, regional sorting results, and production target includes: Based on the order identifier of each backlogged order, obtain the backlogged order quantity; Based on the warehouses awaiting production, the time of production waiting, the sites awaiting production, the backlog of orders, the warehouse capacity, the available site capacity, and the production target, a dynamic decision-making model is constructed. Based on the dynamic decision-making model, the target production schedule is determined.

5. The method according to claim 4, characterized in that, The dynamic decision-making model is constructed based on the pending production warehouse, pending production time, pending production site, backlog of orders, warehouse capacity, available site capacity, and production target, including: Decision constraints are determined based on the backlog of orders, warehouse capacity, available site capacity, and production target. Based on the warehouses, production times, and production sites to be scheduled, the decision-making objectives are determined. A dynamic decision-making model is constructed based on the decision constraints and the decision objective.

6. The method according to claim 5, characterized in that, The method further includes: Based on the target production schedule, determine the remaining site capacity of each site and the remaining warehouse capacity of each warehouse; Based on the remaining capacity of each site, the capacity of each site is adjusted to obtain the adjusted site capacity. Based on the remaining warehouse capacity of each warehouse, the warehouse capacity of each warehouse is adjusted to obtain the adjusted warehouse capacity.

7. An order scheduling device, characterized in that, The device includes: The receiving module is used to receive a request message for production scheduling, the request message carrying the warehouse to be scheduled, the time to be scheduled, and the site to be scheduled; The acquisition module is used to acquire backlog order information for each backlog order in the backlog order set, warehouse information for each warehouse in the warehouse set, and site information for each site in the site set. The first determining module is used to determine a target production schedule based on the backlog order information, warehouse information and site information. The target production schedule is the target orders that the warehouse to be scheduled will pre-produce to the site to be scheduled during the scheduled production time. The sending module is used to send the target production schedule in a response message to the terminal, so that the terminal can schedule the target order according to the target production schedule; The acquisition module is further configured to acquire the order identifier, order time, production warehouse location, production warehouse, and delivery station of each backlogged order in the backlogged order set; determine the order identifier, order time, production warehouse location, production warehouse, and delivery station of each backlogged order as the backlogged order information of each backlogged order; acquire the warehouse capacity and location of each warehouse in the warehouse set; determine the warehouse capacity and location of each warehouse as the warehouse information of each warehouse; acquire the available site capacity, target delivery volume, and location of each site in the site set; determine the available site capacity, target delivery volume, and location of each site as the site information of each site.

8. An electronic device, characterized in that, include: processor; as well as Memory for storing computer programs that can run on the processor; When the computer program is executed by the processor, it implements the steps of the order scheduling method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The device stores computer-executable instructions configured to perform the steps of the order scheduling method according to any one of claims 1 to 6.

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