Logistics data processing method, device, electronic device and storage medium

Abstract

An embodiment of the present application provides a logistics data processing method, device, electronic device, and storage medium. In the embodiment of the present application, the actual completion time, initial planned completion time, and final planned completion time of each logistics operation node for the delivered orders are maintained and managed. Based on these data of the delivered orders, each logistics operation node can be globally coordinated and scheduled, effectively ensuring the timeliness of the logistics fulfillment of subsequent orders to be delivered.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence technology, and particularly to a method, apparatus, electronic device, and storage medium for processing logistics data. Background Art

[0002] As the shopping form of community group buying becomes more and more popular, consumers have higher and higher requirements for logistics fulfillment, and timely fulfillment directly affects logistics costs and user experience. Generally, the logistics operation process of community group buying is as follows: The goods ordered by consumers provided by suppliers are first collected in the central warehouse, then transported from the central warehouse through trunk transportation to the grid warehouse, and finally transported from the grid warehouse through branch transportation to the pick-up point for consumers to pick up the goods at the pick-up point, thus completing the logistics distribution task of the goods. At present, to ensure the timeliness of logistics fulfillment, it is mainly to conduct reasonable scheduling manually throughout the logistics process to complete the logistics operation tasks in a timely manner. However, this manual scheduling method has low efficiency and is difficult to effectively ensure the timeliness of logistics fulfillment. Summary of the Invention

[0003] Multiple aspects of this application provide a method, apparatus, electronic device, and storage medium for processing logistics data to accurately and timely conduct logistics scheduling, thereby effectively ensuring the timeliness of logistics fulfillment.

[0004] An embodiment of this application provides a method for processing logistics data, including: determining the initial planned completion time for each of multiple logistics operation nodes to plan to complete a to-be-delivered order according to the delivery fulfillment time of the to-be-delivered order; during the delivery process of the to-be-delivered order, recording the actual completion time for each logistics operation node to actually complete the to-be-delivered order; for any logistics operation node, if the actual completion time of its previous logistics operation node exceeds the corresponding initial planned completion time, re-determining the final planned completion time of this logistics operation node; according to the actual completion time, initial planned completion time, and final planned completion time of multiple logistics operation nodes for the to-be-delivered orders that have been delivered, conducting logistics scheduling for subsequent order deliveries for each logistics operation node.

[0005] An embodiment of the present application further provides a logistics data processing device, including: a determination module, configured to determine the initial planned completion time for each of multiple logistics operation nodes to complete a to-be-delivered order according to the delivery fulfillment time of the to-be-delivered order; a recording module, configured to record the actual completion time for each logistics operation node to complete the to-be-delivered order during the delivery process of the to-be-delivered order; the determination module is further configured to, for any logistics operation node, if the actual completion time of its previous logistics operation node exceeds the corresponding initial planned completion time, re-determine the final planned completion time of this logistics operation node; a scheduling module, configured to perform logistics scheduling for subsequent order deliveries for each logistics operation node according to the actual completion time, initial planned completion time, and final planned completion time of the to-be-delivered order that has been delivered by multiple logistics operation nodes.

[0006] An embodiment of the present application further provides an electronic device, including: a memory and a processor; the memory is configured to store a computer program; the processor is coupled to the memory and is configured to execute the computer program to perform the steps in the logistics data processing method.

[0007] An embodiment of the present application further provides a computer storage medium storing a computer program, which, when executed by a processor, causes the processor to be able to implement the steps in the logistics data processing method.

[0008] In the embodiment of the present application, maintaining and managing the actual completion time, initial planned completion time, and final planned completion time of each logistics operation node for the delivered order, based on these data of the delivered order, can globally coordinate and schedule each logistics operation node, effectively ensuring the timeliness of the logistics fulfillment of subsequent to-be-delivered orders. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application. In the drawings:

[0010] Figure 1 is a link diagram of an exemplary logistics full link;

[0011] Figure 2 is another link diagram of an exemplary logistics full link;

[0012] Figure 3 is a schematic diagram of an application scenario applicable to a logistics data processing method provided by an embodiment of the present application;

[0013] Figure 4 is a flowchart of a logistics data processing method provided by an embodiment of the present application;

[0014] Figure 5 It is a relational diagram of exemplary work sheets and planned information;

[0015] Figure 6 It is a schematic structural diagram of a logistics data processing device provided by an embodiment of the present application;

[0016] Figure 7 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0017] To make the objectives, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be clearly and completely described below in conjunction with specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only a part rather than all of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0018] First, the terms involved in the present application are introduced.

[0019] The cut-off time of the day refers to the time for switching from the current working day to the next working day. In the embodiments of the present application, the cut-off time of the day for logistics scheduling refers to the time for switching logistics working days. For example, at 22:00:00 every day, the previous logistics working day ends and the next logistics working day begins. That is, the cut-off time of 22:00:00 every day is the switching time between the two working days before and after.

[0020] Central warehouse: It is the core warehouse distribution logistics station, mainly concentrating all goods in the warehouse, sorting according to the SKU (Stock Keeping Unit) of the grid warehouse, and then delivering them to the grid warehouse.

[0021] Grid warehouse: It refers to the transfer warehouse distribution logistics station between the central warehouse and the pick-up point.

[0022] Pick-up point: It refers to the network point established by the e-commerce company offline for customers to pick up packages.

[0023] Trunk line: It refers to the transportation line from the central warehouse to the grid warehouse.

[0024] Branch line: It refers to the transportation line from the grid warehouse to the pick-up point.

[0025] Logistics fulfillment time: It refers to the agreed time for delivering the goods purchased by the consumer to the consumer. Usually, this logistics fulfillment time refers to the agreed time for delivering the goods purchased by the consumer to the pick-up point.

[0026] Logistics operation node: It refers to the node that undertakes the logistics operation task.

[0027] Full logistics link: It refers to the link of the logistics distribution of goods. Usually, the full logistics link is divided into multiple logistics stages, and each logistics stage includes one or more logistics operation nodes. For example, see Figure 1 , the full logistics link is divided into the following logistics stages: supplier stage, central warehouse stage, trunk line stage, grid warehouse stage, self-pickup point stage, and consumer stage. See Figure 2 , in the order of logistics distribution, the full logistics link successively includes the following multiple logistics operation nodes: the purchase and warehousing node responsible for the purchase and warehousing of goods, the order placement and payment node responsible for order placement and payment, the fulfillment and order receiving node responsible for fulfillment and order receiving, the logistics collaboration node, the warehouse order receiving node responsible for warehouse order receiving, the wave occupancy node responsible for order classification, the picking node responsible for picking, the packing node responsible for packing the goods, the sorting node responsible for sorting the goods, the cage sealing node responsible for sealing the goods in a cage, the goods concentration node responsible for concentrating the goods, the shipping node responsible for shipping the goods, the trunk line pickup node responsible for picking up the goods on the trunk line, the trunk line transportation node responsible for transporting the goods on the trunk line, the trunk line arrival node responsible for transporting the goods to the grid warehouse, the grid warehouse sorting node responsible for sorting the goods in the grid warehouse, the grid warehouse shipping node responsible for shipping the goods from the grid warehouse, the branch departure node responsible for the goods leaving the branch line, the transportation node responsible for transporting the goods on the branch line, and the branch arrival node responsible for the goods arriving at the self-pickup point.

[0028] Among them, from the purchase and warehousing node to the wave occupancy node, it can be divided into the supplier stage. From the picking node to the goods concentration node, it can be divided into the central warehouse stage. From the shipping node to the trunk line arrival node, it can be divided into the trunk line stage. From the grid warehouse sorting node to the grid warehouse shipping node, it is divided into the grid warehouse stage; from the branch departure node to the branch arrival node, it is divided into the branch line stage.

[0029] Figure 3 It is a schematic diagram of an application scenario applicable to a logistics data processing method provided in an embodiment of this application. Please refer to Figure 3 , the terminal device 10 can interact with the server 20 through a wired network or a wireless network. For example, the wired network can include coaxial cables, twisted pairs, and optical fibers, etc. The wireless network can be a 2G network, 3G network, 4G network, or 5G network, Wireless Fidelity (WIFI) network, etc. This application does not limit the specific type or specific form of the interaction, as long as it can achieve the function of the interaction between the terminal device 10 and the server 20. Optionally, the terminal device 10 includes, for example, but is not limited to, mobile phones, tablets, laptops, wearable devices, in-vehicle devices. The server 20 includes, for example, but is not limited to, a single server or a distributed server cluster composed of multiple servers. It should be understood that Figure 3The numbers of the terminal devices 10 and the servers 20 in [it] are merely illustrative. In practical applications, any number of terminal devices 10 and servers 20 can be deployed according to actual requirements.

[0030] In practical applications, a user opens a shopping App (application) provided by an e-commerce platform on the terminal device 10. The application interface of the shopping App displays graphic and text information of multiple commodities. The user selects one or more commodities from the multiple commodities and clicks the "submit order" control to submit an order to the server 20 of the e-commerce platform. As Figure 3 shown in ① in [it], when the terminal device 10 submits an order to the server of the e-commerce platform, it sends the order placing time of the order to the server 20 of the e-commerce platform. As Figure 3 shown in ② in [it], after receiving the submitted order, the server 20 of the e-commerce platform determines the logistics fulfillment time for delivering the order based on the order placing time of the order, and performs logistics scheduling based on the logistics fulfillment time. During the logistics scheduling process, the server 20 first determines the initial planned completion time of each logistics operation node based on the logistics fulfillment time. Then, it records the actual completion time of each logistics operation node. For any logistics operation node, if the previous logistics operation node times out, it recalculates the final planned completion time of this logistics operation node. Finally, based on the actual completion time, the initial planned completion time, and the final planned completion time of the multiple logistics operation nodes for the orders that have been delivered, it performs logistics scheduling for the subsequent orders to be delivered for each logistics operation node.

[0031] In this embodiment, for any logistics operation node, if the actual completion time of this logistics operation node is greater than its corresponding initial planned completion time, it is considered that this logistics operation node times out, and at this time, it is necessary to recalculate the final planned completion time of this logistics operation node. If the actual completion time of this logistics operation node is less than or equal to its corresponding initial planned completion time, it is considered that this logistics operation node is normal and does not time out, and at this time, it is not necessary to recalculate the final planned completion time of this logistics operation node.

[0032] Currently, to ensure the timeliness of logistics fulfillment, it is mainly to perform reasonable scheduling manually throughout the logistics process to complete the logistics operation tasks in a timely manner. However, this manual scheduling method has low efficiency and is difficult to effectively ensure the timeliness of logistics fulfillment. For this reason, the embodiments of the present application provide a logistics data processing method, device, electronic device, and storage medium. In this embodiment, the actual completion time, the initial planned completion time, and the final planned completion time of each logistics operation node for the orders that have been delivered are maintained and managed. Based on these data of the orders that have been delivered, each logistics operation node can be globally coordinated and scheduled, effectively ensuring the timeliness of logistics fulfillment for the subsequent orders to be delivered.

[0033] The following will, in conjunction with the accompanying drawings, elaborate in detail on the technical solutions provided by the embodiments of the present application.

[0034] Figure 4 It is a flowchart of a logistics data processing method provided by an embodiment of the present application. This method can be executed by a logistics data processing device, which can be implemented in software and / or hardware and is generally integrated in an electronic device. Refer to Figure 4 , this method may include the following steps:

[0035] 401. Determine the initial planned completion time for each of the multiple logistics operation nodes to complete the to-be-delivered order according to the delivery fulfillment time of the to-be-delivered order.

[0036] 402. During the delivery process of the to-be-delivered order, record the actual completion time for each logistics operation node to complete the to-be-delivered order.

[0037] 403. For any logistics operation node, if the actual completion time of its previous logistics operation node exceeds the corresponding initial planned completion time, re-determine the final planned completion time of this logistics operation node.

[0038] 404. According to the actual completion time, initial planned completion time, and final planned completion time of the multiple logistics operation nodes for the to-be-delivered orders that have been delivered, perform logistics scheduling for subsequent to-be-delivered orders for each logistics operation node.

[0039] Specifically, several to-be-delivered orders can be obtained periodically, at regular intervals, or when a trigger condition set as needed is met for logistics delivery. Among them, a to-be-delivered order refers to an order submitted by a user that has not yet undergone logistics delivery, and the order generally includes a series of real-time order data such as product information, preferential information, user information, receiving information, payment information, and order placement time. Usually, for the convenience of order management and maintenance, an e-commerce platform adds newly submitted orders by users to an order pool. At this time, several to-be-delivered orders can be obtained from the order pool for logistics delivery.

[0040] After obtaining the order to be delivered, the delivery fulfillment time of the order to be delivered can be determined based on the order placement time of the order to be delivered according to actual application requirements. For example, the order placement time of the order to be delivered is 2021-09-21 21:00:00, and the daily cut-off time of the logistics scheduling is 22:00:00 every day. Combining the order placement time of the order to be delivered and the daily cut-off time of the logistics scheduling, it is determined that the delivery fulfillment time of the order to be delivered is from 2021-09-22 12:00:00 to 2021-09-22 20:00:00. Among them, 2021-09-22 12:00:00 is the expected delivery time, and 2021-09-22 20:00:00 is the latest delivery time. As long as the order to be delivered is delivered to the consumer at any time before the latest delivery time, it can be considered that the order to be delivered has completed the logistics fulfillment in a timely manner. If the order to be delivered is delivered to the consumer after the latest delivery time, it can be considered that the order to be delivered has not completed the logistics fulfillment.

[0041] After determining the delivery fulfillment time of the order to be delivered, the initial planned completion times for each of the multiple logistics operation nodes to complete the order to be delivered can be determined according to the delivery fulfillment time of the order to be delivered. As an optional implementation method, when determining the initial planned completion time, the time period between the daily cut-off time of the logistics scheduling and the delivery fulfillment time can be divided to obtain the operation time intervals between any two adjacent logistics operation nodes; according to the daily cut-off time and each operation time interval, the initial planned completion times for each of the multiple logistics operation nodes to complete the order to be delivered are calculated.

[0042] It should be noted that the time period between the daily cut-off time of the logistics scheduling and the delivery fulfillment time can be reasonably divided by combining information such as the scale of each logistics operation node, the logistics operation capacity, and the number of orders that have not been processed yet. In addition, the operation time interval from the daily cut-off time to the first logistics operation node in the entire logistics link can also be set flexibly. After determining each operation time interval, adding each operation time interval to the daily cut-off time in sequence can obtain the initial planned completion times of each logistics operation node on the entire logistics link. For example, see Figure 3, taking 22:00:00 on September 21, 2021 as the time starting point and 12:00:00 on September 22, 2021 as the time end point, assuming that the cage closing node in the central warehouse stage is the first logistics operation node on the entire logistics chain, the operation time interval between the cage closing node in the central warehouse stage and the time cut-off is 14 hours, the operation time interval between the cage closing node in the central warehouse stage and the goods collection node in the central warehouse stage is 20 minutes, the operation time interval between the goods collection node in the central warehouse stage and the trunk line delivery node in the trunk line stage is 4 hours, the operation time interval between the trunk line delivery node in the trunk line stage and the grid warehouse operation completion node in the grid warehouse stage is 4 hours, and the operation time interval between the grid warehouse operation completion node in the grid warehouse stage and the branch line delivery node in the branch line stage is 3 hours and 40 minutes. Then the initial planned completion time of the cage closing node in the central warehouse stage is 00:00:00 on September 22, 2021, the initial planned completion time of the goods collection node in the central warehouse stage is 00:20:00 on September 22, 2021, the initial planned completion time of the trunk line delivery node in the trunk line stage is 04:20:00 on September 22, 2021, the initial planned completion time of the grid warehouse operation completion node in the grid warehouse stage is 08:20:00 on September 22, 2021, and the initial planned completion time of the branch line delivery node in the branch line stage is 12:00:00 on September 22, 2021.

[0043] In this implementation, after the to-be-delivered order completes the corresponding material operation task at any logistics operation node, record the actual completion time when the logistics operation node actually completes the to-be-delivered order. If the actual completion time of the logistics operation node for the to-be-delivered order is greater than the initial planned completion time, determine whether the logistics operation node has exceeded the time limit for operation. If the actual completion time of the logistics operation node for the to-be-delivered order is less than or equal to the initial planned completion time, determine that the logistics operation node has not exceeded the time limit for operation.

[0044] In this implementation, for any logistics operation node, if the actual completion time of its previous logistics operation node exceeds the corresponding initial planned completion time, re-determine the final planned completion time of this logistics operation node. For example, in Figure 3Among them, the initial planned completion time of the cage sealing node in the central warehouse stage is 2021-09-22 00:00:00, and the actual completion time of the cage sealing node in the central warehouse stage is 2021-09-22 00:20:00. Since the cage sealing node exceeded the time limit by 20 minutes, the final planned completion time of the goods collection node was updated to 2021-09-22 00:40:00. The actual completion time of the goods collection node is 2022-09-22 00:50:00. Since the goods collection node exceeded the time limit by 50 minutes, the final planned completion time of the main line arrival node was updated to 2021-09-22 04:50:00. It should be noted that with the update of the final planned completion time of a certain logistics operation node, the intermediate planned completion times of other logistics operation nodes behind this logistics operation node can also be updated. The intermediate planned completion time is the planned completion time between the initial planned completion time and the final planned completion time. For example, in Figure 3 Among them, after the cage sealing node of the central warehouse exceeded the time limit, the final planned completion time of the goods collection node was updated, as well as the intermediate planned completion times of several nodes such as the main line delivery node, the grid warehouse operation completion node, and the branch line delivery node. After the goods collection node of the central warehouse exceeded the time limit, the final planned completion time of the main line delivery node was updated, as well as the intermediate planned completion times of several nodes such as the grid warehouse operation completion node and the branch line delivery node.

[0045] In this embodiment, the final planned completion time of this logistics operation node can be re-determined in combination with the overtime times of each logistics operation node before this logistics operation node. As an example, re-determining the final planned completion time of this logistics operation node includes: calculating the actual completion time and the corresponding initial planned completion time of the previous logistics operation node of this logistics operation node to obtain the overtime time of the previous logistics operation node of this logistics operation node; obtaining the final planned completion time of this logistics operation node according to the overtime time of the previous logistics operation node of this logistics operation node and the initial planned completion time of this logistics operation node. It should be noted that in this example, the overtime time refers to the time difference between the actual completion time of the logistics operation node and its corresponding initial planned completion time.

[0046] As another example, re-determining the final planned completion time of the logistics operation node includes: determining the overtime logistics operation nodes whose actual completion time is greater than the final planned completion time and their overtime times; accumulating the overtime times of each overtime logistics operation node to obtain the accumulated overtime time; and determining the final planned completion time of the logistics operation node according to the actual completion time and the accumulated overtime time of the logistics operation node. In this example, the overtime time refers to the time difference between the actual completion time of the logistics operation node and its corresponding final planned completion time. It should be noted that for any logistics operation node, if the actual completion time of its previous logistics operation node does not exceed the corresponding initial planned completion time, the initial planned completion time of this logistics operation node does not need to be updated. At this time, the initial planned completion time of the logistics operation node can be used as the final planned completion time of this logistics operation node.

[0047] In this embodiment, after completing the logistics distribution tasks for each to-be-delivered order, according to the actual completion time, initial planned completion time, and final planned completion time of multiple logistics operation nodes for the to-be-delivered orders that have been delivered, logistics scheduling for subsequent order deliveries is performed for each logistics operation node.

[0048] Specifically, big data analysis can be performed on the actual completion time, initial planned completion time, and final planned completion time of multiple logistics operation nodes for the to-be-delivered orders that have been delivered to determine which logistics operation nodes are prone to overtime operations and which are not, and subsequent logistics scheduling of to-be-delivered orders can be guided based on the results of these big data analyses.

[0049] The logistics data processing method provided by the embodiments of this application maintains and manages the actual completion time, initial planned completion time, and final planned completion time of each logistics operation node for the delivered orders. Based on these data of the delivered orders, it can overall plan and schedule each logistics operation node globally, effectively ensuring the timeliness of logistics performance for subsequent to-be-delivered orders.

[0050] In practical applications, at the granularity of a single logistics operation node, based on the actual completion time, initial planned completion time, and final planned completion time of each logistics operation node for the delivered orders, identify the logistics operation nodes with frequent overtime operations and the logistics operation nodes with occasional overtime operations, and guide the logistics scheduling of subsequent to-be-delivered orders based on the identification results. It is also possible to, at the granularity of a single logistics stage, based on the actual completion time, initial planned completion time, and final planned completion time of each logistics operation node for the delivered orders, identify the logistics stages with frequent overtime operations and the logistics stages with occasional overtime operations, and guide the logistics scheduling of subsequent to-be-delivered orders based on the identification results, but it is not limited thereto.

[0051] Therefore, further optionally, the implementation manner of step 404 may be: after the order to be delivered has been delivered, determine the overtime type of each logistics stage for each delivered order according to the actual completion time, initial planned completion time, and final planned completion time of multiple logistics operation nodes in each logistics stage for each delivered order; during the subsequent order delivery process, according to the overtime types of each logistics stage for at least one delivered order, with the goal of reducing the overtime time of the entire logistics link, schedule each logistics operation node of each logistics stage.

[0052] In practical applications, the overtime categories of each logistics stage for each delivered order can be flexibly set as needed. As an example, when determining the overtime category of each logistics stage for each delivered order, if the actual completion time of the last logistics operation node in each logistics stage for each delivered order is greater than the corresponding final planned completion time, it is determined that the overtime category of this logistics stage for each delivered order is the first category; if the actual completion time of the last logistics operation node in each logistics stage for each delivered order is greater than the corresponding initial planned completion time and less than the corresponding final planned completion time, it is determined that the overtime category of this logistics stage for each delivered order is the second category. If the actual completion time of the last logistics operation node in each logistics stage for each delivered order is less than the corresponding initial planned completion time, it is determined that the overtime category of this logistics stage for each delivered order is the third category.

[0053] It should be noted that when the overtime category of a logistics stage for each delivered order is the first category, it indicates that the entire logistics stage has overtime operations, and this type of overtime operation is relatively serious. When the overtime category of a logistics stage for each delivered order is the second category, it indicates that the entire logistics stage has overtime operations, and this type of overtime operation is relatively not very serious. When the overtime category of a logistics stage for each delivered order is the third category, it indicates that the entire logistics stage has not had overtime operations.

[0054] Take Figure 3 as an example to illustrate. If the number of delivered orders for which the central warehouse stage has completed the delivery task is 5, then determine the overtime category of the central warehouse stage for each delivered order according to the actual completion time, initial planned completion time, and final planned completion time of the last goods collection node in the central warehouse stage for each delivered order. Since the overtime situations of the central warehouse stage for each delivered order are different, in this way, the corresponding overtime categories of the 5 delivered orders may be the first category, the second category, or the third category.

[0055] In this embodiment, after determining the timeout types for at least one delivered order in each logistics stage, during the subsequent order delivery process, each logistics operation node in each logistics stage can be scheduled with the goal of reducing the timeout time of the entire logistics link according to the timeout types for at least one delivered order in each logistics stage. In specific applications, the timeout types for at least one delivered order in each logistics stage can be analyzed to determine which logistics stages frequently have type-one timeout operations, which logistics stages frequently have type-two timeout operations, and which logistics stages frequently have type-three normal operations (i.e., non-timeout operations). Based on these analysis results, during the subsequent order delivery process, each logistics operation node in each logistics stage can be selectively invoked.

[0056] Further optionally, to perform accurate and objective logistics scheduling, during the subsequent order delivery process, with the goal of reducing the timeout time of the entire logistics link, when scheduling each logistics operation node in each logistics stage by combining the first count and the second count corresponding to each logistics stage, the first count of type-one timeouts and the second count of type-two timeouts that occur for each logistics stage for at least one delivered order can be determined according to the timeout type of each logistics stage for each delivered order; during the subsequent order delivery process, each logistics operation node in each logistics stage can be scheduled with the goal of reducing the timeout time of the entire logistics link by combining the first count and the second count corresponding to each logistics stage.

[0057] Specifically, when determining the first count of type-one timeouts that occur for each logistics stage for at least one delivered order, it is sequentially determined whether the timeout type of each logistics stage for each delivered order is type-one. If so, the first count is incremented by one. Similarly, when determining the second count of type-two timeouts that occur for each logistics stage for at least one delivered order, it is sequentially determined whether the timeout type of each logistics stage for each delivered order is type-two. If so, the second count is incremented by one. For example, the number of delivered orders for which the delivery task has been completed in the central warehouse stage is 5. Among them, for 2 of the 5 delivered orders, the corresponding timeout category is type-one, so the first count is 2; for 2 of the 5 delivered orders, the corresponding timeout category is type-two, so the second count is 2.

[0058] After determining the first number of first-category timeouts and the second number of second-category timeouts for at least one delivered order in each logistics stage, the various logistics operation nodes of these various logistics stages can be called more distinctively in the subsequent order delivery process. Therefore, further optionally, in the subsequent order delivery process, the scheduling goal is to reduce the timeout time of the entire logistics link, and when scheduling the various logistics operation nodes of each logistics stage in combination with the first number and the second number corresponding to each logistics stage, the scheduling goal can be to reduce the timeout time of the entire logistics link, and according to the first number and the second number corresponding to each logistics stage, the various logistics operation nodes of each logistics stage can be prompted to reduce the timeout time for subsequent order delivery, wherein the more the first number, the greater the prompt intensity of the corresponding logistics stage; when the first number is the same, the more the second number, the greater the prompt intensity of the corresponding logistics stage.

[0059] The embodiment of the present application does not limit the form of prompt intensity. For example, prompt intensity may refer to the number of prompts, or to the severity of the prompt content. The severity of the prompt content may be set according to actual application requirements. For example, the severity of the prompt content is associated with the overtime fine amount in the prompt content. The greater the overtime fine amount, the greater the severity of the prompt content.

[0060] In actual applications, some logistics operation nodes in a logistics stage may operate overtime, while some logistics operation nodes may not operate overtime. Therefore, further optionally, in order to call each logistics operation node in each logistics stage more distinctively, when prompting each logistics operation node in each logistics stage to reduce the overtime time for subsequent order delivery, the overtime logistics operation node in each logistics stage can be prompted to reduce the overtime time for subsequent order delivery; wherein, the more overtime logistics operation nodes whose actual completion time is greater than the initial planned completion time, the greater the corresponding prompt intensity, and the third number is increased by one when the overtime logistics operation node times out for each delivered order.

[0061] In order to better understand the logistics data processing method provided in the embodiment of the present application, it is explained below in conjunction with a scenario embodiment.

[0062] Scenario Example:

[0063] In the community group-buying scenario of selling vegetables, at least the actual completion time, initial planned completion time and final planned completion time of each order of each logistics operation node can be recorded in the operation sheet corresponding to each logistics operation node, which will help to improve the certainty of logistics fulfillment timeliness, realize SLA (Service-Level Agreement), and coordinate the operation time of each logistics operation node in the entire logistics chain.

[0064] The work order refers to an electronic document that carries information, and the work order may include but is not limited to the following fields:

[0065] The order type (relate_biz_type) field is used to describe the type of the work order, which includes but is not limited to: central warehouse work order, central warehouse delivery order, grid warehouse work order, and group order. A group order is a list of goods and quantities sent to a pick-up point on a logistics fulfillment date. Each pick-up point has its own corresponding group order.

[0066] Order number (relate_biz_id) field: used to describe the specific document number of the work order, which is the unique identifier of the work order, for example, the central warehouse work order number that identifies the uniqueness of the central warehouse work order, the grid warehouse work order number that identifies the uniqueness of the grid warehouse work order, and the group order number that identifies the uniqueness of the group order.

[0067] Node group (node_group) field: used to describe the logistics stage to which the logistics operation node corresponding to the work order belongs. In actual production, many logistics operation nodes are carried out in the same logistics stage. For example, picking, packing, and cage sealing are all carried out in the central warehouse. After picking, packing, cage sealing and other operations are completed, the goods will be handed over to the transport for shipment. Therefore, the various logistics operation nodes belonging to the central warehouse stage are grouped and classified as the central warehouse stage.

[0068] Node type (node_type) field: used to describe the type of logistics operation node corresponding to the work order. Node types include, but are not limited to: picking node, packing node, distribution node, cage sealing node, etc.

[0069] Node order (node_order) field: used to describe the order of the logistics operation nodes corresponding to the work order in the entire logistics chain. In actual applications, the logistics operation nodes in the entire logistics chain have an order of precedence. For example, the trunk transport node must be before the branch transport node.

[0070] Plan version (plan_version) field: used to describe the version information of the planned completion time. When the field value of the plan version (plan_version) field is 0, it means that the corresponding planned completion time is the initial planned completion time. When the planned completion time is recalculated due to timeout, when a new planned completion time is generated, the corresponding field value is increased by 1. Therefore, the larger the field value of the plan version (plan_version) field, the newer the version of the planned completion time.

[0071] Plan time (plan_check_time) field: used to record and describe the plan completion time. The recorded plan completion time can be accurate to the minute level.

[0072] In this scenario embodiment, at least the actual completion time, initial planned completion time, and final planned completion time of each logistics operation node for each order are recorded in the work order corresponding to each logistics operation node, and segmented assessment and full-link assessment can also be supported. Among them, segmented assessment refers to an independent assessment of a single logistics stage. Full-link assessment refers to an assessment of each logistics stage of the entire logistics chain. Through the assessment method, it is possible to promote the reduction of overtime time in overtime logistics stages or overtime logistics operation nodes, thereby effectively ensuring the timeliness of logistics fulfillment.

[0073] In actual applications, through segmented assessment and full-link assessment, the operation time of the central warehouse can be extended by up to 2 hours while ensuring that the fulfillment time remains unchanged; the overtime ratio of several key logistics operation nodes such as trunk line arrival, branch line departure, and branch line arrival has dropped by about 50%. In addition, it supports both recalculation of the planned completion time of each logistics operation node and retention of various versions of the planned completion time of each logistics operation node, so that different versions of the planned completion time can be used for relevant analysis in different scenarios.

[0074] Combine the following Figure 5 , the relationship between the work order and planning information of community group buying of vegetable sales is introduced. Figure 5 The direction of the arrow in is the generation order of each work order; the quantity relationship of the work order is represented by 1:1 (indicating 1 to 1), N:1 (indicating many to 1), and M:N (indicating many to many); the information pointed to by the dotted arrow indicates what planning information is recorded on the work order, for example, the central warehouse work order and logistics order record the full-link planning information, the group order records the grid warehouse planning information and branch line planning information, and the TC work order records the trunk line planning information. Among them, the TC work order refers to the trunk line transport order, and the TC delivery order is the trunk line delivery order. The full-link planning information refers to the operation planning information of each logistics operation node on the full link (for example, including the planned completion time of each version), the grid warehouse planning information refers to the operation planning information of each logistics operation node in the grid warehouse stage, the branch line planning information refers to the operation planning information of each logistics operation node in the branch warehouse stage, and the trunk line planning information refers to the operation planning information of each logistics operation node in the trunk line stage.

[0075] Figure 6 A schematic diagram of the structure of a logistics data processing device provided in an embodiment of the present application. Figure 6 The device may include: a determination module 61, a recording module 62 and a scheduling module 63.

[0076] A determination module 61 is used to determine the initial planned completion time of the multiple logistics operation nodes to complete the orders to be delivered according to the delivery fulfillment time of the orders to be delivered;

[0077] The recording module 62 is used to record the actual completion time of each logistics operation node in the delivery process of the order to be delivered;

[0078] The determination module 61 is also used to re-determine the final planned completion time of any logistics operation node if the actual completion time of the previous logistics operation node exceeds the corresponding initial planned completion time;

[0079] The scheduling module 63 is used to perform logistics scheduling for subsequent order delivery for each logistics operation node based on the actual completion time, initial planned completion time and final planned completion time of the delivered orders to be delivered by multiple logistics operation nodes.

[0080] Further optionally, when determining module 61 to determine the initial planned completion time for each of the multiple logistics operation nodes to complete the order to be delivered based on the delivery fulfillment time of the order to be delivered, it is specifically used to: divide the time period between the daily cut time and the delivery fulfillment time of the logistics scheduling to obtain the operation time interval between any two adjacent logistics operation nodes; calculate the initial planned completion time for each of the multiple logistics operation nodes to complete the order to be delivered based on the daily cut time and each operation time interval.

[0081] Further optionally, when determining that module 61 re-determines the final planned completion time of the logistics operation node, it is specifically used to: calculate the actual completion time of the previous logistics operation node of the logistics operation node and the corresponding initial planned completion time to obtain the timeout time of the previous logistics operation node of the logistics operation node; obtain the final planned completion time of the logistics operation node based on the timeout time of the previous logistics operation node of the logistics operation node and the initial planned completion time of the logistics operation node.

[0082] Further optionally, when determining module 61 to re-determine the final planned completion time of the logistics operation node, it is specifically used to: determine the overtime logistics operation nodes and their timeout times whose actual completion time is greater than the final planned completion time; accumulate the timeout times of each overtime logistics operation node to obtain the accumulated timeout time; and determine the final planned completion time of the logistics operation node based on the actual completion time and the accumulated timeout time of the logistics operation node.

[0083] Further optionally, the scheduling module 63 performs logistics scheduling for subsequent order delivery for each logistics operation node based on the actual completion time, initial planned completion time and final planned completion time of the delivered orders to be delivered by multiple logistics operation nodes. Specifically, it is used to: after the delivery of the orders to be delivered has been completed, determine the timeout type for each delivered order in each logistics stage according to the actual completion time, initial planned completion time and final planned completion time for each delivered order by multiple logistics operation nodes in each logistics stage; in the subsequent order delivery process, schedule each logistics operation node in each logistics stage according to the timeout type for at least one delivered order in each logistics stage, with the scheduling goal of reducing the timeout time of the entire logistics chain.

[0084] Further optionally, the scheduling module 63 determines the timeout category for each delivered order in each logistics stage based on the actual completion time, initial planned completion time and final planned completion time for each delivered order by multiple logistics operation nodes in each logistics stage. Specifically, if the actual completion time for each delivered order by the last logistics operation node in each logistics stage is greater than the corresponding final planned completion time, then the timeout category for each delivered order in the logistics stage is determined to be the first category; if the actual completion time for each delivered order by the last logistics operation node in each logistics stage is greater than the corresponding initial planned completion time and less than the corresponding final planned completion time, then the timeout category for each delivered order in the logistics stage is determined to be the second category.

[0085] Further optionally, in the subsequent order delivery process, the scheduling module 63, based on the timeout type for at least one delivered order in each logistics stage, takes reducing the timeout time of the entire logistics chain as the scheduling goal, when scheduling each logistics operation node in each logistics stage, is specifically used to: determine the first number of first category timeouts and the second number of second category timeouts for at least one delivered order in each logistics stage according to the timeout type for each delivered order in each logistics stage; in the subsequent order delivery process, taking reducing the timeout time of the entire logistics chain as the scheduling goal, schedule each logistics operation node in each logistics stage in combination with the first number and the second number corresponding to each logistics stage.

[0086] Further optionally, in the process of subsequent order delivery, the scheduling module 63 takes reducing the timeout time of the entire logistics link as the scheduling goal, and schedules each logistics operation node of each logistics stage in combination with the first number and the second number corresponding to each logistics stage. Specifically, it is used to: take reducing the timeout time of the entire logistics link as the scheduling goal, and according to the first number and the second number corresponding to each logistics stage, prompt each logistics operation node of each logistics stage to reduce the timeout time for subsequent order delivery, wherein, the more the first number, the greater the prompt intensity of the corresponding logistics stage; when the first number is the same, the more the second number, the greater the prompt intensity of the corresponding logistics stage.

[0087] Further optionally, when the scheduling module 63 prompts each logistics operation node in each logistics stage to reduce the timeout time for subsequent order delivery, it is specifically used to: prompt the overtime logistics operation nodes in each logistics stage to reduce the timeout time for subsequent order delivery; wherein, the more the third number of overtime logistics operation nodes whose actual completion time is greater than the initial planned completion time, the greater the corresponding prompt intensity, and the third number is increased by one when the overtime logistics operation node times out for each delivered order.

[0088] Figure 6 The logistics data processing device shown can execute Figure 4 The implementation principle and technical effect of the logistics data processing method of the embodiment shown are not repeated here. The specific way in which each module and unit performs operations in the logistics data processing device in the above embodiment has been described in detail in the embodiment of the method, and will not be elaborated here.

[0089] It should be noted that the execution subject of each step of the method provided in the above embodiment can be the same device, or the method can be executed by different devices. For example, the execution subject of steps 401 to 403 can be device A; for another example, the execution subject of steps 401 and 402 can be device A, and the execution subject of steps 403 and 404 can be device B; and so on.

[0090] In addition, in some of the processes described in the above embodiments and the accompanying drawings, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel, and the sequence numbers of the operations, such as 401, 402, etc., are only used to distinguish between different operations, and the sequence numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0091] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 7 As shown, the electronic device includes: a memory 71 and a processor 72;

[0092] The memory 71 is used to store computer programs and can be configured to store various other data to support operations on the computing platform. Examples of such data include instructions for any application or method operating on the computing platform, contact data, phone book data, messages, pictures, videos, etc.

[0093] The memory 71 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0094] The processor 72 is coupled to the memory 71 and is used to execute the computer program in the memory 71, so as to: determine the initial planned completion time for each of the multiple logistics operation nodes to complete the order to be delivered according to the delivery fulfillment time of the order to be delivered; during the delivery process of the order to be delivered, record the actual completion time of each logistics operation node to complete the order to be delivered; for any logistics operation node, if the actual completion time of its previous logistics operation node exceeds the corresponding initial planned completion time, re-determine the final planned completion time of the logistics operation node; and perform logistics scheduling for subsequent order delivery for each logistics operation node according to the actual completion time, initial planned completion time and final planned completion time of the order to be delivered that has been delivered by multiple logistics operation nodes.

[0095] Further optionally, when the processor 72 determines the initial planned completion time for each of the multiple logistics operation nodes to complete the order to be delivered based on the delivery fulfillment time of the order to be delivered, it is specifically used to: divide the time period between the daily cut time and the delivery fulfillment time of the logistics scheduling to obtain the operation time interval between any two adjacent logistics operation nodes; calculate the initial planned completion time for each of the multiple logistics operation nodes to complete the order to be delivered based on the daily cut time and each operation time interval.

[0096] Further optionally, when determining that module 61 re-determines the final planned completion time of the logistics operation node, it is specifically used to: calculate the actual completion time of the previous logistics operation node of the logistics operation node and the corresponding initial planned completion time to obtain the timeout time of the previous logistics operation node of the logistics operation node; obtain the final planned completion time of the logistics operation node based on the timeout time of the previous logistics operation node of the logistics operation node and the initial planned completion time of the logistics operation node.

[0097] Further optionally, when the processor 72 redetermines the final planned completion time of the logistics operation node, it is specifically used to: determine the overtime logistics operation nodes and their timeout times whose actual completion time is greater than the final planned completion time; accumulate the timeout times of each overtime logistics operation node to obtain the accumulated timeout time; and determine the final planned completion time of the logistics operation node based on the actual completion time and the accumulated timeout time of the logistics operation node.

[0098] Further optionally, when the processor 72 performs logistics scheduling for subsequent order delivery for each logistics operation node based on the actual completion time, initial planned completion time and final planned completion time of the delivered orders to be delivered by multiple logistics operation nodes, it is specifically used to: after the delivery of the orders to be delivered has been completed, determine the timeout type for each delivered order in each logistics stage according to the actual completion time, initial planned completion time and final planned completion time of each delivered order by multiple logistics operation nodes in each logistics stage; in the subsequent order delivery process, schedule each logistics operation node in each logistics stage according to the timeout type for at least one delivered order in each logistics stage, with the scheduling goal of reducing the timeout time of the entire logistics chain.

[0099] Further optionally, the processor 72 determines the timeout category for each delivered order in each logistics stage based on the actual completion time, initial planned completion time and final planned completion time for each delivered order by multiple logistics operation nodes in each logistics stage, and is specifically used to: if the actual completion time for each delivered order by the last logistics operation node in each logistics stage is greater than the corresponding final planned completion time, then it is determined that the timeout category for each delivered order in the logistics stage is the first category; if the actual completion time for each delivered order by the last logistics operation node in each logistics stage is greater than the corresponding initial planned completion time and less than the corresponding final planned completion time, then it is determined that the timeout category for each delivered order in the logistics stage is the second category.

[0100] Further optionally, in the subsequent order delivery process, the processor 72 schedules each logistics operation node of each logistics stage based on the timeout type for at least one delivered order in each logistics stage with the scheduling goal of reducing the timeout time of the entire logistics chain. Specifically, it is used to: determine the first number of first category timeouts and the second number of second category timeouts for at least one delivered order in each logistics stage according to the timeout type for each delivered order in each logistics stage; in the subsequent order delivery process, schedule each logistics operation node of each logistics stage based on the first number and the second number corresponding to each logistics stage with the scheduling goal of reducing the timeout time of the entire logistics chain.

[0101] Further optionally, during the subsequent order delivery process, the processor 72 takes reducing the timeout time of the entire logistics link as the scheduling goal, and schedules each logistics operation node of each logistics stage in combination with the first number and the second number corresponding to each logistics stage. Specifically, it is used to: take reducing the timeout time of the entire logistics link as the scheduling goal, and according to the first number and the second number corresponding to each logistics stage, prompt each logistics operation node of each logistics stage to reduce the timeout time for subsequent order delivery, wherein, the more the first number, the greater the prompt intensity of the corresponding logistics stage; when the first number is the same, the more the second number, the greater the prompt intensity of the corresponding logistics stage.

[0102] Further optionally, when the processor 72 prompts each logistics operation node in each logistics stage to reduce the timeout time for subsequent order delivery, it is specifically used to: prompt the overtime logistics operation nodes in each logistics stage to reduce the timeout time for subsequent order delivery; wherein, the more the third number of overtime logistics operation nodes whose actual completion time is greater than the initial planned completion time, the greater the corresponding prompt intensity, and the third number is increased by one when the overtime logistics operation node times out for each delivered order.

[0103] For the detailed implementation process of the processor executing each action, please refer to the relevant description in the aforementioned method embodiment, which will not be repeated here.

[0104] Further, if Figure 7 As shown, the electronic device also includes: a communication component 73, a display 74, a power component 75, an audio component 76 and other components. Figure 7 Only some components are shown schematically, which does not mean that the electronic device only includes Figure 7 In addition, Figure 7The components in the dashed box are optional components, not mandatory components, and the specific components depend on the product form of the electronic device. The electronic device of this embodiment can be implemented as a terminal device such as a desktop computer, a laptop computer, a smart phone, or an IOT device, or a server device such as a conventional server, a cloud server, or a server array. If the electronic device of this embodiment is implemented as a terminal device such as a desktop computer, a laptop computer, a smart phone, etc., it can include Figure 7 If the electronic device of this embodiment is implemented as a server device such as a conventional server, a cloud server or a server array, it may not include Figure 7 Components within the dashed box.

[0105] For the detailed implementation process of the processor executing each action, please refer to the relevant description in the aforementioned method embodiment or device embodiment, which will not be repeated here.

[0106] Accordingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program, which, when executed, can implement each step that can be executed by an electronic device in the above method embodiment.

[0107] Accordingly, an embodiment of the present application also provides a computer program product, including a computer program / instruction. When the computer program / instruction is executed by a processor, the processor is enabled to implement each step in the above method embodiment that can be executed by an electronic device.

[0108] The above-mentioned communication component is configured to facilitate wired or wireless communication between the device where the communication component is located and other devices. The device where the communication component is located can access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G / LTE, 5G and other mobile communication networks, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0109] The above-mentioned display includes a screen, and the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

[0110] The power supply assembly provides power to various components of the device where the power supply assembly is located. The power supply assembly may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device where the power supply assembly is located.

[0111] The above-mentioned audio component can be configured to output and / or input audio signals. For example, the audio component includes a microphone (MIC), and when the device where the audio component is located is in an operating mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in a memory or sent via a communication component. In some embodiments, the audio component also includes a speaker for outputting an audio signal.

[0112] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0113] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0114] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0115] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0116] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0117] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0118] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0119] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0120] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for processing logistics data, characterized in that, it includes: Determine the initial planned completion time for each of multiple logistics operation nodes to complete the to-be-delivered order according to the delivery fulfillment time of the to-be-delivered order; During the delivery process of the to-be-delivered order, record the actual completion time for each logistics operation node to complete the to-be-delivered order; For any logistics operation node, if the actual completion time of its previous logistics operation node exceeds the corresponding initial planned completion time, re-determine the final planned completion time of this logistics operation node; After the to-be-delivered order has been delivered, determine the overtime type for each logistics stage for each delivered order according to the actual completion time, initial planned completion time, and final planned completion time of multiple logistics operation nodes in each logistics stage for each delivered order; According to the overtime type for each logistics stage for each delivered order, determine the first number of times of the first type of overtime and the second number of times of the second type of overtime for each logistics stage for at least one delivered order; During the subsequent order delivery process, with the goal of reducing the overtime time of the entire logistics link, schedule each logistics operation node in each logistics stage by combining the corresponding first number and second number of times of each logistics stage.

2. The method according to claim 1, characterized in that, Determining the initial planned completion time for each of multiple logistics operation nodes to complete the to-be-delivered order according to the delivery fulfillment time of the to-be-delivered order includes: Divide the time period between the daily cut-off time of logistics scheduling and the delivery fulfillment time to obtain the operation time intervals between any two adjacent logistics operation nodes; Calculate the initial planned completion time for each of multiple logistics operation nodes to complete the to-be-delivered order according to the daily cut-off time and each operation time interval.

3. The method according to claim 1, characterized in that, Re-determining the final planned completion time of this logistics operation node includes: Calculate the actual completion time of the previous logistics operation node of this logistics operation node and the corresponding initial planned completion time to obtain the overtime time of the previous logistics operation node of this logistics operation node; According to the overtime time of the previous logistics operation node of this logistics operation node and the initial planned completion time of this logistics operation node, obtain the final planned completion time of this logistics operation node.

4. The method according to claim 1, characterized in that, Re-determining the final planned completion time of this logistics operation node includes: Determine the overtime logistics operation nodes whose actual completion time is greater than the final planned completion time and their overtime times; Accumulate the overtime times of each overtime logistics operation node to obtain the accumulated overtime time; According to the actual completion time of this logistics operation node and the accumulated overtime time, determine the final planned completion time of this logistics operation node.

5. The method according to claim 1, characterized in that, Determining the overtime category for each logistics stage for each delivered order according to the actual completion time, initial planned completion time, and final planned completion time of multiple logistics operation nodes in each logistics stage for each delivered order includes: If the actual completion time of the last logistics operation node in each logistics stage for each delivered order is greater than the corresponding final planned completion time, it is determined that the overtime category of this logistics stage for each delivered order is the first category; If the actual completion time of the last logistics operation node in each logistics stage for each delivered order is greater than the corresponding initial planned completion time and less than the corresponding final planned completion time, it is determined that the overtime category of this logistics stage for each delivered order is the second category.

6. The method according to claim 1, wherein, In the subsequent order delivery process, with the goal of reducing the overtime time of the entire logistics link, each logistics operation node of each logistics stage is scheduled in combination with the first number and the second number corresponding to each logistics stage, including: With the goal of reducing the overtime time of the entire logistics link, according to the first number and the second number corresponding to each logistics stage, each logistics operation node of each logistics stage is prompted to reduce the overtime time for the subsequent order delivery, wherein, the more the first number, the greater the prompting intensity of the corresponding logistics stage; in the case where the first numbers are the same, the more the second number, the greater the prompting intensity of the corresponding logistics stage.

7. The method according to claim 6, wherein, Prompting each logistics operation node of each logistics stage to reduce the overtime time for the subsequent order delivery includes: Prompting the overtime logistics operation nodes in each logistics stage to reduce the overtime time for the subsequent order delivery; among them, the overtime logistics operation node with the more third number of actual completion time greater than the initial planned completion time has a greater corresponding prompting intensity, and the third number is incremented by one in the case where the overtime logistics operation node has overtime for each delivered order.

8. A logistics data processing device, wherein, including: A determination module, configured to determine the initial planned completion time for each of a plurality of logistics operation nodes to plan to complete the to-be-delivered order according to the delivery fulfillment time of the to-be-delivered order; A recording module, configured to record the actual completion time of each logistics operation node for actually completing the to-be-delivered order during the delivery process of the to-be-delivered order; The determination module is further configured to, for any logistics operation node, if the actual completion time of its previous logistics operation node exceeds the corresponding initial planned completion time, re-determine the final planned completion time of this logistics operation node; A scheduling module, configured to, after the to-be-delivered order has been delivered, determine the overtime type of each logistics stage for each delivered order according to the actual completion time, initial planned completion time, and final planned completion time of a plurality of logistics operation nodes in each logistics stage for each delivered order; Determine the first number of times of the first - type timeout and the second number of times of the second - type timeout that occur in each logistics stage for at least one delivered order according to the timeout type of each delivered order in each logistics stage; during the subsequent order delivery process, with the goal of reducing the timeout time of the entire logistics link, schedule each logistics operation node in each logistics stage by combining the first number of times and the second number of times corresponding to each logistics stage.

9. An electronic device, Characterized in that, Comprising: A memory and a processor; The memory is used for storing a computer program; The processor is coupled to the memory and is used for executing the computer program to perform the steps in the method according to any one of claims 1 - 7.

10. A computer storage medium storing a computer program, Characterized in that, When the computer program is executed by a processor, it causes the processor to be able to implement the steps in the method according to any one of claims 1 - 7.

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