A task allocation method and system for fabric supply chain

Abstract

The embodiment of the present invention provides a method and system for allocating tasks in a fabric supply chain, which performs task allocation scheduling and parsing on the task allocation nodes corresponding to the emergency supply chain members of the preset task implementation plan of the schedulable task allocation nodes, records the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan, and then calculates the task implementation allocation data of the task implementation network model of the task implementation plan through the task implementation progress information, task implementation logic information and task implementation allocation data of the task implementation plan, thereby loading the task allocation directional data of the task implementation plan in the information of multiple task supply chain members through the task implementation progress information, task implementation logic information and task implementation allocation data of the task implementation plan. In this way, considering the relationship between the task implementation plan and the task allocation node, the efficiency of task allocation can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fabric supply chain, and in particular to a method and system for allocating tasks in a fabric supply chain. Background Art

[0002] At present, in the process of task allocation for fabric supply chain operation plan, the relationship between some task implementation plans and task allocation nodes is not taken into account, which leads to low efficiency of task allocation for fabric supply chain operation plan. Summary of the invention

[0003] In view of this, an object of an embodiment of the present invention is to provide a method and system for allocating tasks in a fabric supply chain, which can effectively improve the efficiency of task allocation in a fabric supply chain operation plan.

[0004] In a first aspect, an embodiment of the present invention provides a task allocation method for a fabric supply chain, which is applied to a task allocation service platform. The method includes:

[0005] Acquire multiple supply chain task information of the fabric supply chain operation plan, and acquire multiple task supply chain member information and multiple task supply chain member allocation node information from the multiple supply chain task information;

[0006] Determine the task allocation node corresponding to the emergency supply chain member from the plurality of task supply chain member information, and obtain the schedulable task allocation node according to the task allocation node corresponding to the emergency supply chain member;

[0007] Perform task allocation scheduling analysis on the task allocation nodes corresponding to the emergency supply chain members of the preset task implementation plan of the schedulable task allocation nodes, and record the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan;

[0008] Calculate through the task implementation logic information of the task implementation plan and the allocation node information of the multiple task supply chain members, access the target task implementation plan in sequence, and calculate the task implementation allocation data of the task implementation network model of the task implementation plan;

[0009] The task implementation plan's task allocation directional data is loaded into the plurality of task supply chain member information through the task implementation progress information of the task implementation plan, the task implementation logic information of the task implementation plan and the task implementation allocation data of the task implementation network model of the task implementation plan.

[0010] The step of obtaining the schedulable task allocation node according to the task allocation node corresponding to the emergency supply chain member includes:

[0011] The task allocation nodes corresponding to the emergency supply chain members are input into a preset deep learning neural network to obtain the non-schedulable task allocation nodes and the schedulable task allocation nodes.

[0012] The preset deep learning neural network is obtained by performing AI feature learning on the first calibration data set and the second calibration data set that are generated in real time and acquired in advance, specifically including:

[0013] The task allocation nodes corresponding to the emergency supply chain members of each task implementation plan and the task allocation nodes corresponding to the emergency supply chain members of non-task implementation plans are analyzed by clustering to determine the task allocation nodes corresponding to the task implementation plans and the emergency supply chain members of non-task implementation plans, so as to train the deep learning neural network.

[0014] The step of determining the task allocation node corresponding to the urgent supply chain member from the plurality of task supply chain member information comprises:

[0015] Task allocation nodes are matched with member feature data of each task supply chain member in the plurality of task supply chain member information to obtain task allocation nodes corresponding to the urgent supply chain members of the member feature data of each task supply chain member.

[0016] Among them, the task allocation scheduling analysis is performed on the task allocation node corresponding to the emergency supply chain member of the preset task implementation plan of the schedulable task allocation node, and the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan are recorded, including:

[0017] Analyze the task allocation nodes corresponding to the emergency supply chain members of the determined task implementation plan, perform task allocation scheduling analysis on the task allocation nodes corresponding to the emergency supply chain members between the member characteristic data of different task supply chain members, determine the member characteristic data of the task implementation plan in each task supply chain member, and record the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan.

[0018] Another aspect of the present invention is to provide a task allocation system for a fabric supply chain, which is applied to a task allocation service platform. The system includes:

[0019] An acquisition module, used to acquire multiple supply chain task information of a fabric supply chain operation plan, and acquire multiple task supply chain member information and multiple task supply chain member allocation node information from the multiple supply chain task information;

[0020] A determination module, used to determine the task allocation node corresponding to the emergency supply chain member from the information of the plurality of task supply chain members, and obtain the schedulable task allocation node according to the task allocation node corresponding to the emergency supply chain member;

[0021] A recording module is used to perform task allocation scheduling analysis on the task allocation nodes corresponding to the emergency supply chain members of the preset task implementation plan of the schedulable task allocation nodes, and record the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan;

[0022] A calculation module, used to perform calculations based on the task implementation logic information of the task implementation plan and the allocation node information of the multiple task supply chain members, sequentially access the target task implementation plan, and calculate the task implementation allocation data of the task implementation network model of the task implementation plan;

[0023] A loading module is used to load the task implementation plan's task allocation directional data into the multiple task supply chain member information through the task implementation progress information of the task implementation plan, the task implementation logic information of the task implementation plan and the task implementation allocation data of the task implementation network model of the task implementation plan.

[0024] The task allocation method and system of the fabric supply chain provided by the embodiment of the present invention determines the task allocation node corresponding to the emergency supply chain member from multiple task supply chain member information, obtains the schedulable task allocation node according to the task allocation node corresponding to the emergency supply chain member, then performs task allocation scheduling analysis on the schedulable task allocation node through the task allocation node corresponding to the emergency supply chain member of the preset task implementation plan, records the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan, and then calculates through the task implementation logic information of the task implementation plan and the allocation node information of multiple task supply chain members, sequentially accesses the target task implementation plan, and calculates the task implementation allocation data of the task implementation network model of the task implementation plan, thereby loading the task allocation directional data of the task implementation plan in the multiple task supply chain member information through the task implementation progress information, task implementation logic information and task implementation allocation data of the task implementation plan, so as to perform task allocation on the fabric supply chain operation plan. In this way, considering the relationship between the task implementation plan and the task allocation node, the task allocation efficiency of the fabric supply chain operation plan can be effectively improved.

[0025] In order to make the above-mentioned objects, features and advantages of the embodiments of the present invention more obvious and easy to understand, the embodiments will be described in detail below in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 A schematic diagram showing a flow chart of a method for allocating tasks in a fabric supply chain provided by an embodiment of the present invention;

[0028] Figure 2 A functional module block diagram of a task allocation system for a fabric supply chain provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0029] In order to enable students in this technical field to better understand the scheme of the present invention, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all of the embodiments. According to the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0030] The terms "first", "second", "third", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Figure 1 A flow chart of a method for allocating tasks in a fabric supply chain provided by an embodiment of the present invention is shown. The method for allocating tasks in a fabric supply chain can be executed by a task allocation service platform.

[0032] The task allocation service platform may include one or more processors, such as one or more central processing units (CPUs), each of which may implement one or more hardware threads. The task allocation service platform may also include any storage medium for storing any type of information such as code, settings, data, etc. Non-limitingly, for example, the storage medium may include any one or more combinations of the following: any type of RAM, any type of ROM, flash memory device, hard disk, optical disk, etc. More generally, any storage medium may use any technology to store information. Further, any storage medium may provide volatile or non-volatile retention of information. Further, any storage medium may represent a fixed or removable component of the task allocation service platform. In one case, when the processor executes an associated instruction stored in any storage medium or a combination of storage media, the task allocation service platform may perform any operation of the associated instruction. The task allocation service platform also includes one or more drive units for interacting with any storage medium, such as a hard disk drive unit, an optical disk drive unit, etc.

[0033] The task allocation service platform also includes an input / output (I / O) for receiving various inputs (via an input unit) and for providing various outputs (via an output unit). A specific output mechanism may include a presentation device and an associated graphical user interface (GUI). The task allocation service platform may also include one or more network interfaces for exchanging data with other devices via one or more communication units. One or more communication buses couple the components described above together.

[0034] The communication unit can be implemented in any manner, for example, through a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. The communication unit can include any combination of hardwired links, wireless links, routers, gateway functions, name task distribution service platforms, etc., governed by any protocol or combination of protocols.

[0035] The following is an introduction to the detailed steps of the task allocation method for the fabric supply chain.

[0036] Step 100, obtaining a plurality of supply chain task information of a fabric supply chain operation plan, and obtaining a plurality of task supply chain member information and a plurality of task supply chain member allocation node information from the plurality of supply chain task information.

[0037] Step 200: determine the task allocation node corresponding to the emergency supply chain member from the information of the plurality of task supply chain members, and obtain the schedulable task allocation node according to the task allocation node corresponding to the emergency supply chain member.

[0038] Step 300, performing task allocation scheduling analysis on the task allocation nodes corresponding to the emergency supply chain members of the preset task implementation plan of the schedulable task allocation nodes, and recording the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan.

[0039] Step 400, calculates through the task implementation logic information of the task implementation plan and the allocation node information of the multiple task supply chain members, accesses the target task implementation plan in sequence, and calculates the task implementation allocation data of the task implementation network model of the task implementation plan.

[0040] Step 500, loading the task allocation directional data of the task implementation plan into the plurality of task supply chain member information through the task implementation progress information of the task implementation plan, the task implementation logic information of the task implementation plan and the task implementation allocation data of the task implementation network model of the task implementation plan.

[0041] In summary, this embodiment determines the task allocation node corresponding to the emergency supply chain member from multiple task supply chain member information, obtains the schedulable task allocation node according to the task allocation node corresponding to the emergency supply chain member, then performs task allocation scheduling analysis on the schedulable task allocation node through the task allocation node corresponding to the emergency supply chain member of the preset task implementation plan, records the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan, and then calculates through the task implementation logic information of the task implementation plan and the allocation node information of multiple task supply chain members, sequentially accesses the target task implementation plan, and calculates the task implementation allocation data of the task implementation network model of the task implementation plan, thereby loading the task allocation directional data of the task implementation plan in the multiple task supply chain member information through the task implementation progress information, task implementation logic information and task implementation allocation data of the task implementation plan. In this way, considering the relationship between the task implementation plan and the task allocation node, the task allocation efficiency can be improved.

[0042] Among them, for step 200, this embodiment can specifically input the task allocation node corresponding to the emergency supply chain member into a preset deep learning neural network to obtain the non-schedulable task allocation node and the schedulable task allocation node.

[0043] Among them, the preset deep learning neural network is obtained by performing AI feature learning on the first calibration data set and the second calibration data set that are pre-acquired and generated in real time. For example, the task allocation nodes corresponding to the emergency supply chain members of each task implementation plan and the task allocation nodes corresponding to the emergency supply chain members of the non-task implementation plan can be grouped and analyzed to determine the task allocation nodes corresponding to the task implementation plan and the emergency supply chain members of the non-task implementation plan, so as to train the deep learning neural network.

[0044] Among them, for step 200, this embodiment can specifically perform task allocation node matching on the member characteristic data of each task supply chain member in the multiple task supply chain member information to obtain the task allocation node corresponding to the emergency supply chain member of the member characteristic data of each task supply chain member.

[0045] Among them, for step 300, this embodiment can specifically analyze the task allocation nodes corresponding to the emergency supply chain members of the determined task implementation plan, perform task allocation scheduling analysis on the task allocation nodes corresponding to the emergency supply chain members between the member characteristic data of different task supply chain members, determine the member characteristic data of the task implementation plan in each task supply chain member and record the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan.

[0046] Figure 2 The functional module diagram of the task allocation system of the fabric supply chain provided by the embodiment of the present invention is shown. The functions implemented by the task allocation system of the fabric supply chain can correspond to the steps executed by the above method. The task allocation system of the fabric supply chain can be understood as the above task allocation service platform, or the processor of the task allocation service platform, or can be understood as a component independent of the above task allocation service platform or processor that implements the functions of the present invention under the control of the task allocation service platform. The functions of each functional module of the task allocation system of the fabric supply chain are described in detail below.

[0047] The acquisition module 201 is used to acquire multiple supply chain task information of the fabric supply chain operation plan, and acquire multiple task supply chain member information and multiple task supply chain member allocation node information from the multiple supply chain task information.

[0048] The determination module 202 is used to determine the task allocation node corresponding to the emergency supply chain member from the multiple task supply chain member information, and obtain the schedulable task allocation node according to the task allocation node corresponding to the emergency supply chain member.

[0049] The recording module 203 is used to perform task allocation scheduling analysis on the task allocation nodes corresponding to the emergency supply chain members of the preset task implementation plan of the schedulable task allocation nodes, and record the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan.

[0050] The calculation module 204 is used to perform calculations based on the task implementation logic information of the task implementation plan and the allocation node information of the multiple task supply chain members, access the target task implementation plan in sequence, and calculate the task implementation allocation data of the task implementation network model of the task implementation plan.

[0051] The loading module 205 is used to load the task allocation directional data of the task implementation plan into the multiple task supply chain member information through the task implementation progress information of the task implementation plan, the task implementation logic information of the task implementation plan and the task implementation allocation data of the task implementation network model of the task implementation plan.

[0052] The determining module 202 obtains the schedulable task allocation node in the following manner:

[0053] The task allocation nodes corresponding to the emergency supply chain members are input into a preset deep learning neural network to obtain the non-schedulable task allocation nodes and the schedulable task allocation nodes.

[0054] The preset deep learning neural network is obtained by performing AI feature learning on the first calibration data set and the second calibration data set that are generated in real time and acquired in advance, and the specific method includes:

[0055] The task allocation nodes corresponding to the emergency supply chain members of each task implementation plan and the task allocation nodes corresponding to the emergency supply chain members of non-task implementation plans are analyzed by clustering to determine the task allocation nodes corresponding to the task implementation plans and the emergency supply chain members of non-task implementation plans, so as to train the deep learning neural network.

[0056] The method of determining the task allocation node corresponding to the urgent supply chain member from the plurality of task supply chain member information includes:

[0057] Task allocation nodes are matched with member feature data of each task supply chain member in the plurality of task supply chain member information to obtain task allocation nodes corresponding to the urgent supply chain members of the member feature data of each task supply chain member.

[0058] The recording module 203 can perform task allocation scheduling analysis on the task allocation nodes corresponding to the emergency supply chain members of the preset task implementation plan of the schedulable task allocation nodes, and record the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan in the following manner:

[0059] Analyze the task allocation nodes corresponding to the emergency supply chain members of the determined task implementation plan, perform task allocation scheduling analysis on the task allocation nodes corresponding to the emergency supply chain members between the member characteristic data of different task supply chain members, determine the member characteristic data of the task implementation plan in each task supply chain member, and record the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan.

[0060] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0061] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device and method embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0062] In addition, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0063] Alternatively, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a task allocation service platform or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, task allocation service platform or data center. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a task allocation service platform, a data center, etc. that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (eg, a solid state disk (SSD)).

[0064] It should be noted that, in this article, the terms "comprise", "include" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0065] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered in all respects as exemplary and non-restrictive, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations within the meaning and scope of the equivalent elements of the claims be included in the invention. Any drawings in the claims should not be considered as limiting the claims to which they relate.

Claims

1. A task allocation method for a fabric supply chain, characterized in that: Applied to a task allocation service platform, the method comprises: Acquire multiple supply chain task information of the fabric supply chain operation plan, and acquire multiple task supply chain member information and multiple task supply chain member allocation node information from the multiple supply chain task information; Determine the task allocation node corresponding to the emergency supply chain member from the plurality of task supply chain member information, and obtain the schedulable task allocation node according to the task allocation node corresponding to the emergency supply chain member; Perform task allocation scheduling analysis on the task allocation nodes corresponding to the emergency supply chain members of the preset task implementation plan of the schedulable task allocation nodes, and record the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan; Calculate through the task implementation logic information of the task implementation plan and the allocation node information of the multiple task supply chain members, access the target task implementation plan in sequence, and calculate the task implementation allocation data of the task implementation network model of the task implementation plan; Loading the task allocation directional data of the task implementation plan into the plurality of task supply chain member information through the task implementation progress information of the task implementation plan, the task implementation logic information of the task implementation plan and the task implementation allocation data of the task implementation network model of the task implementation plan, so as to allocate tasks to the fabric supply chain operation plan; The obtaining of the schedulable task allocation node according to the task allocation node corresponding to the emergency supply chain member includes: Inputting the task allocation nodes corresponding to the emergency supply chain members into a preset deep learning neural network to obtain non-schedulable task allocation nodes and the schedulable task allocation nodes; The preset deep learning neural network is obtained by performing AI feature learning on the first calibration data set and the second calibration data set that are generated in real time and acquired in advance, and specifically includes: Based on the first calibration data set and the second calibration data set, the task allocation nodes corresponding to the emergency supply chain members of each task implementation plan and the task allocation nodes corresponding to the emergency supply chain members of the non-task implementation plan are analyzed by clustering, the task allocation nodes corresponding to the task implementation plan and the emergency supply chain members of the non-task implementation plan are determined, and the deep learning neural network is obtained based on the training; The step of determining the task allocation node corresponding to the urgent supply chain member from the plurality of task supply chain member information includes: Perform task allocation node matching on member feature data of each task supply chain member in the plurality of task supply chain member information to obtain a task allocation node corresponding to an emergency supply chain member of the member feature data of each task supply chain member; The task allocation scheduling and parsing of the schedulable task allocation node corresponding to the emergency supply chain member of the preset task implementation plan is performed, and the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan are recorded, including: Analyze the task allocation nodes corresponding to the emergency supply chain members of the determined task implementation plan, perform task allocation scheduling analysis on the task allocation nodes corresponding to the emergency supply chain members between the member characteristic data of different task supply chain members, determine the member characteristic data of the task implementation plan in each task supply chain member, and record the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan.

2. A task allocation system for a fabric supply chain, characterized in that: Applied to a task allocation service platform, the system includes: An acquisition module, used to acquire multiple supply chain task information of a fabric supply chain operation plan, and acquire multiple task supply chain member information and multiple task supply chain member allocation node information from the multiple supply chain task information; A determination module, used to determine the task allocation node corresponding to the emergency supply chain member from the information of the plurality of task supply chain members, and obtain the schedulable task allocation node according to the task allocation node corresponding to the emergency supply chain member; A recording module is used to perform task allocation scheduling analysis on the task allocation nodes corresponding to the emergency supply chain members of the preset task implementation plan of the schedulable task allocation nodes, and record the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan; A calculation module, used to perform calculations based on the task implementation logic information of the task implementation plan and the allocation node information of the multiple task supply chain members, sequentially access the target task implementation plan, and calculate the task implementation allocation data of the task implementation network model of the task implementation plan; A loading module, used to load the task allocation directional data of the task implementation plan into the plurality of task supply chain member information through the task implementation progress information of the task implementation plan, the task implementation logic information of the task implementation plan and the task implementation allocation data of the task implementation network model of the task implementation plan, so as to perform task allocation on the fabric supply chain operation plan; The determination module is specifically used for: Inputting the task allocation nodes corresponding to the emergency supply chain members into a preset deep learning neural network to obtain non-schedulable task allocation nodes and the schedulable task allocation nodes; The preset deep learning neural network is obtained by performing AI feature learning on the first calibration data set and the second calibration data set that are generated in real time and acquired in advance, and specifically includes: Performing group analysis on the task allocation nodes corresponding to the emergency supply chain members of each task implementation plan and the task allocation nodes corresponding to the emergency supply chain members of the non-task implementation plan, determining the task allocation nodes corresponding to the task implementation plan and the emergency supply chain members of the non-task implementation plan, and obtaining the deep learning neural network based on the training; The determination module is specifically used for: Perform task allocation node matching on member feature data of each task supply chain member in the plurality of task supply chain member information to obtain a task allocation node corresponding to an emergency supply chain member of the member feature data of each task supply chain member; The recording module is specifically used for: Analyze the task allocation nodes corresponding to the emergency supply chain members of the determined task implementation plan, perform task allocation scheduling analysis on the task allocation nodes corresponding to the emergency supply chain members between the member characteristic data of different task supply chain members, determine the member characteristic data of the task implementation plan in each task supply chain member, and record the task implementation progress information of the task implementation plan and the task implementation logic information of the task implementation plan.

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