Supply chain intelligent scheduling method and system

Abstract

The invention discloses an intelligent scheduling method and system for a supply chain. The intelligent scheduling method for the supply chain comprises the following steps: acquiring real-time data of the supply chain; preprocessing the real-time data to obtain effective data; defining a scheduling rule, and processing effective data according to the scheduling rule to obtain a scheduling scheme; and executing the scheduling scheme. Through real-time data acquisition and processing, the timeliness and accuracy of a scheduling decision are ensured; a user is allowed to customize a scheduling rule to adapt to actual requirements of different enterprises; an artificial intelligence algorithm is used for intelligent decision making, and the scheduling accuracy and efficiency are improved; and access and processing of multi-source data are supported, and expansion and upgrading are easy.

Description

Technical Field

[0001] The present invention relates to the field of logistics technology, and in particular to a supply chain intelligent scheduling method and system. Background Art

[0002] In modern society, with the increase of business complexity and the intensification of market competition, higher requirements are placed on the efficiency and accuracy of resource scheduling. At present, there are many scheduling methods on the market, but most of them lack real-time data support and intelligent decision-making capabilities, resulting in low scheduling efficiency and failure to meet the needs of modern business. The present invention aims to provide a method for intelligent scheduling based on real-time data analysis and customized scheduling rules to overcome the shortcomings of the prior art.

[0003] The common scheduling methods on the market mainly rely on preset scheduling rules and manual intervention. These methods use preset rules to make preliminary allocations of resources, but when encountering special circumstances or changes in demand, manual intervention and adjustment are often required. In addition, some advanced scheduling systems have begun to try to introduce data analysis technology, but existing scheduling systems are often unable to obtain and analyze data in real time, resulting in delayed scheduling decisions and unable to meet the real-time requirements of modern business; and existing technologies allocate resources based on preset scheduling rules, which are often unable to adapt to complex and changeable actual situations, resulting in low scheduling efficiency; at the same time, the system lacks intelligent decision-making capabilities and cannot make automated decisions and optimizations based on real-time data and other relevant information, limiting the development space of the scheduling system. Summary of the invention

[0004] In view of the problems of weak real-time performance, low efficiency and inability to make intelligent decisions in current scheduling methods, the present invention provides a supply chain intelligent scheduling method, which can effectively improve the efficiency, real-time performance and accuracy of scheduling by acquiring real-time data, customizing scheduling rules and making intelligent decisions through artificial intelligence algorithms.

[0005] To achieve the above object, the embodiments of the present invention adopt the following technical solutions:

[0006] A supply chain intelligent scheduling method comprises the following steps:

[0007] Get real-time data on the supply chain;

[0008] Preprocessing the real-time data to obtain valid data;

[0009] Defining scheduling rules, processing valid data according to the scheduling rules, and obtaining a scheduling plan;

[0010] The scheduling scheme is executed.

[0011] According to one aspect of the present invention, the real-time data of the supply chain is obtained by obtaining real-time data from any one or more of orders, logistics providers, and carriers of the supply chain.

[0012] According to one aspect of the present invention, the real-time data includes at least: order information, transportation routes, transportation methods, timeliness requirements and carrier information.

[0013] According to one aspect of the present invention, the preprocessing of the real-time data to obtain valid data comprises:

[0014] Clean the real-time data and obtain all data dimensions contained in the real-time data;

[0015] Based on all data dimensions, perform data integration of a single data dimension in turn;

[0016] Analyze and process the integrated data to obtain valid data.

[0017] According to one aspect of the present invention, the defining of scheduling rules comprises:

[0018] Get all data dimensions contained in the valid data;

[0019] Select at least one required data dimension from all data dimensions and define the priority of selecting data dimensions;

[0020] Generate scheduling rules based on the priority of the selected data dimension.

[0021] According to one aspect of the present invention, generating a scheduling rule according to the priority of selecting a data dimension includes: selecting a data dimension of the same priority, selecting any one of integrated scheduling, segmented scheduling, and volume-based scheduling to generate a corresponding scheduling rule

[0022] According to one aspect of the present invention, the processing of valid data according to the scheduling rules to obtain a scheduling solution includes: based on the scheduling rules, processing valid data to obtain an optional scheduling solution.

[0023] According to one aspect of the present invention, the supply chain intelligent scheduling method further includes: obtaining the execution status of the scheduling plan during execution, and adjusting the scheduling plan according to the execution status.

[0024] According to one aspect of the present invention, the supply chain intelligent scheduling method further includes: establishing a scheduling rule base, and storing the scheduling rules defined each time through the scheduling rule base.

[0025] According to one aspect of the present invention, the supply chain intelligent scheduling method further includes: directly selecting scheduling rules from a scheduling rule library, processing valid data according to the scheduling rules, and obtaining a scheduling plan.

[0026] A supply chain intelligent scheduling system, comprising:

[0027] Data collection module, used to obtain real-time data of the supply chain;

[0028] A data processing module, used for preprocessing the real-time data to obtain valid data;

[0029] Rule definition module, used to define scheduling rules;

[0030] An intelligent scheduling module, used to process valid data according to the scheduling rules to obtain a scheduling plan;

[0031] The scheduling execution module is used to execute the scheduling plan.

[0032] Advantages of the present invention: The intelligent scheduling method for supply chain described in the present invention comprises the following steps: obtaining real-time data of the supply chain; preprocessing the real-time data to obtain valid data; defining scheduling rules, processing valid data according to the scheduling rules to obtain a scheduling plan; and executing the scheduling plan. The timeliness and accuracy of scheduling decisions are ensured through real-time data collection and processing; users are allowed to customize scheduling rules to meet the actual needs of different enterprises; artificial intelligence algorithms are used for intelligent decision-making to improve the accuracy and efficiency of scheduling; and multi-source data access and processing are supported, which is easy to expand and upgrade. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 This is a flow chart of the supply chain intelligent scheduling method according to the first embodiment of the present invention;

[0035] Figure 2 This is a flow chart of the supply chain intelligent scheduling method according to the second embodiment of the present invention;

[0036] Figure 3 This is a structural diagram of the supply chain intelligent scheduling system described in Embodiment 3 of the present invention;

[0037] Figure 4 This is a structural diagram of the supply chain intelligent scheduling equipment described in Example 4 of the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] The terms "including" and "having" and any variations thereof in the embodiments of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product or equipment comprising a series of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products or equipment.

[0040] The naming or numbering of the steps in the embodiments of the present invention does not mean that the steps in the method flow must be executed in the time / logical sequence indicated by the naming or numbering. The execution order of the named or numbered process steps can be changed according to the technical purpose to be achieved, as long as the same or similar technical effects can be achieved.

[0041] Reference to an "embodiment" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0042] Embodiment 1

[0043] like Figure 1 As shown, a supply chain intelligent scheduling method includes the following steps:

[0044] Step S1: Obtain real-time data of the supply chain;

[0045] Obtain real-time data of the supply chain, specifically: obtain real-time data from any one or more of the supply chain's orders, logistics providers, drivers, carriers, and carrier platforms.

[0046] Real-time data includes: order information, transportation routes, transportation methods, timeliness requirements and carrier information, etc., as follows:

[0047] Order information includes customer information, project, product type, pickup time, delivery time, and return requirements;

[0048] The transportation route includes the transportation starting point, transportation end point and optional transportation paths;

[0049] The modes of transportation include road transportation, rail transportation, water transportation, air transportation, combined transportation and multimodal transportation;

[0050] Timeliness requirements include transportation timeliness and receipt timeliness;

[0051] Carrier information includes carrier information and driver data. Carrier information includes the carrier's transport routes and route quotations. Driver data includes driver resume, vehicle model, vehicle length information, etc.

[0052] In actual application, the route quotation includes freight, pick-up fee, delivery fee, unloading fee, etc.

[0053] Step S2: preprocessing the real-time data to obtain valid data;

[0054] In practical applications, the real-time data obtained includes multiple data dimensions and a large amount of data, which often contains errors, omissions, duplications, inconsistencies, anomalies and other problems. Directly using the relevant data will affect the accuracy and reliability of the results, so data preprocessing steps such as data cleaning and normalization are required.

[0055] Step S21: clean the real-time data and obtain all data dimensions contained in the real-time data;

[0056] In order to ensure the accuracy and reliability of the acquired data, the acquired real-time data is cleaned, including data deduplication, exception processing, missing data processing, etc.; all data dimensions contained in the cleaned data are analyzed, such as order information, transportation routes, transportation methods, timeliness requirements, carrier information, etc.

[0057] Step S22: performing data integration of a single data dimension in sequence according to all data dimensions;

[0058] According to all the acquired data dimensions, data integration is performed for each data dimension in turn, and the real-time data is first integrated according to a single data dimension;

[0059] Then obtain all the data integrated in a single data dimension and perform secondary data integration. The secondary integration relies on different directions of a single data dimension. For example, the data dimension of order information contains different directions such as customer information, project, type of goods, pick-up time, delivery time, and return efficiency requirements.

[0060] Get the data after secondary integration and classify it in different directions. For example, classify customer information by customer information, and group the data belonging to the same customer into one category. You can use the customer name as the category name.

[0061] Step S23: Analyze and process the integrated data to obtain valid data.

[0062] Further, the integrated data is analyzed. For example, in the direction of customer information in the order information, the customer information that needs to be processed this time is analyzed, and all the data contained in the customer information is used as valid data to facilitate the further formulation and processing of data scheduling plans; similarly, the customer information can also be processed according to classified data such as the project to which it belongs and the type of goods to obtain valid data.

[0063] Valid data does not only have a single direction of a single dimension. In fact, valid data is determined according to needs and can include multiple different directions of different data dimensions.

[0064] Step S3: define scheduling rules, process valid data according to the scheduling rules, and obtain a scheduling plan;

[0065] Scheduling rules are generally defined in advance, and the defined scheduling rules are optimized and adjusted regularly or when needed. That is, scheduling rules only need to be defined when the supply chain intelligent scheduling method is used for the first time, and the scheduling rules are subsequently obtained directly according to actual needs.

[0066] Step S31: Acquire all data dimensions contained in the valid data;

[0067] Step S32: selecting at least one required data dimension from all data dimensions, and defining the priority of selecting the data dimension;

[0068] For example, you can select order information, timeliness requirements, and carrier information as the selected data dimensions, and define the priorities of the selected data dimensions from high to low as timeliness requirements, order information, and carrier information.

[0069] Step S33: Generate a scheduling rule according to the priority of the selected data dimension;

[0070] Furthermore, in step S32, the data dimension with the highest priority is the timeliness requirement. In this embodiment, the timeliness requirements include two directions: transportation timeliness and return order timeliness. The transportation timeliness is taken as the direction with the highest priority in this data dimension, and the priority is further divided according to different data levels in this direction. The reference priority can be divided from high to low into same-day delivery, next-day delivery, and third-day delivery, and then the priority of the return order timeliness is confirmed, and then the priorities of different directions of order information and carrier information are defined in turn.

[0071] Specifically, for data dimensions of the same priority, the scheduling rules may include integrated scheduling, segmented scheduling, and volume-based scheduling.

[0072] Integrated scheduling means defining scheduling rules according to the integration result in step S22, so as to realize scheduling. For example, the scheduling rules may be orders with customer information belonging to the same pickup city and the same pickup time, orders with customer information belonging to the same delivery address and the same pickup time, orders with customer information belonging to the same customer and the same delivery time, etc. These scheduling rules can be realized and integrated scheduling can be performed;

[0073] Split-segment scheduling is generally used to save transportation costs. The same order is split into multiple segments, and then scheduled after multiple sub-orders are integrated. For example, an order is split into a pickup segment, a trunk transportation segment, and a terminal delivery segment, and then separate orders are integrated in each segment. Therefore, split-segment scheduling can define scheduling rules as follows: split the same order into multiple segments, define order integration rules for each segment, and thus implement split-segment scheduling of orders that are split first and then integrated.

[0074] Split-volume scheduling is generally used to improve the loading rate. The same order is split and transported using multiple means of transportation. Data dimensions can also be selected according to actual requirements, and relevant scheduling rules can be defined based on the data dimensions to achieve split-volume scheduling.

[0075] Step S34: Based on the scheduling rules, process the valid data to obtain the available scheduling solutions.

[0076] According to the defined data dimension priorities and priorities in different directions of the data dimensions, the valid data is processed to obtain available scheduling plans. For example, based on step S34, a scheduling plan with the shortest time limit can be obtained. When the time limits are consistent, scheduling plans in different directions such as customer information, project, cargo type, pick-up time, and delivery time can be further obtained.

[0077] In actual applications, the same dispatch rule may have multiple carriers / drivers that meet the dispatch priority. You can further define the carriers or drivers specified for specific customers or routes, match the corresponding carriers / drivers according to the obtained dispatch rules, and adjust the dispatch plan based on the above content.

[0078] Step S4: Execute the scheduling scheme.

[0079] Step S5: Obtain the execution status of the scheduling scheme during execution, and adjust the scheduling scheme according to the execution status.

[0080] The scheduling plan is formulated according to the established scheduling rules. By obtaining the execution status during the execution of the scheduling plan, the scheduling plan can be adjusted, and then the scheduling plan can be optimized in real time to improve the accuracy and efficiency of subsequent scheduling.

[0081] This embodiment provides a supply chain intelligent scheduling method, including the following steps: obtaining real-time data of the supply chain; preprocessing the real-time data to obtain valid data; defining scheduling rules, processing valid data according to the scheduling rules, and obtaining a scheduling plan; and executing the scheduling plan. Through real-time data collection and processing, the timeliness and accuracy of scheduling decisions are ensured; users are allowed to customize scheduling rules to meet the actual needs of different enterprises; artificial intelligence algorithms are used to make intelligent decisions to improve the accuracy and efficiency of scheduling; and multi-source data access and processing are supported, which is easy to expand and upgrade.

[0082] Embodiment 2

[0083] like Figure 2 As shown, a supply chain intelligent scheduling method includes the following steps:

[0084] Step S1: Obtain real-time data of the supply chain;

[0085] Obtain real-time data of the supply chain, specifically: obtain real-time data from any one or more of the supply chain's orders, logistics providers, drivers, carriers, and carrier platforms.

[0086] Real-time data includes: order information, transportation routes, transportation methods, timeliness requirements and carrier information, etc., as follows:

[0087] Order information includes customer information, project, product type, pickup time, delivery time, and return requirements;

[0088] The transportation route includes the transportation starting point, transportation end point and optional transportation paths;

[0089] The modes of transportation include road transportation, rail transportation, water transportation, air transportation, combined transportation and multimodal transportation;

[0090] Timeliness requirements include transportation timeliness and receipt timeliness;

[0091] Carrier information includes carrier information and driver data. Carrier information includes the carrier's transport routes and route quotations. Driver data includes driver resume, vehicle model, vehicle length information, etc.

[0092] In actual application, the route quotation includes freight, pick-up fee, delivery fee, unloading fee, etc.

[0093] Step S2: preprocessing the real-time data to obtain valid data;

[0094] In practical applications, the real-time data obtained includes multiple data dimensions and a large amount of data, which often contains errors, omissions, duplications, inconsistencies, anomalies and other problems. Directly using the relevant data will affect the accuracy and reliability of the results, so data preprocessing steps such as data cleaning and normalization are required.

[0095] Step S21: clean the real-time data and obtain all data dimensions contained in the real-time data;

[0096] In order to ensure the accuracy and reliability of the acquired data, the acquired real-time data is cleaned, including data deduplication, exception processing, missing data processing, etc.; all data dimensions contained in the cleaned data are analyzed, such as order information, transportation routes, transportation methods, timeliness requirements, carrier information, etc.

[0097] Step S22: performing data integration of a single data dimension in sequence according to all data dimensions;

[0098] According to all the acquired data dimensions, data integration is performed for each data dimension in turn, and the real-time data is first integrated according to a single data dimension;

[0099] Then obtain all the data integrated in a single data dimension and perform secondary data integration. The secondary integration relies on different directions of a single data dimension. For example, the data dimension of order information contains different directions such as customer information, project, type of goods, pick-up time, delivery time, and return efficiency requirements.

[0100] Get the data after secondary integration and classify it in different directions. For example, classify customer information by customer information, and group the data belonging to the same customer into one category. You can use the customer name as the category name.

[0101] Step S23: Analyze and process the integrated data to obtain valid data.

[0102] Further, the integrated data is analyzed. For example, in the direction of customer information in the order information, the customer information that needs to be processed this time is analyzed, and all the data contained in the customer information is used as valid data to facilitate the further formulation and processing of data scheduling plans; similarly, the customer information can also be processed according to classified data such as the project to which it belongs and the type of goods to obtain valid data.

[0103] Valid data does not only have a single direction of a single dimension. In fact, valid data is determined according to needs and can include multiple different directions of different data dimensions.

[0104] Step S3: define dispatching rules, process valid data according to the dispatching rules, obtain a dispatching plan, and establish a dispatching rule base to store the dispatching rules defined each time;

[0105] Scheduling rules are generally defined in advance, and the defined scheduling rules are optimized and adjusted regularly or when needed. That is, scheduling rules only need to be defined when the supply chain intelligent scheduling method is used for the first time, and the scheduling rules are subsequently obtained directly according to actual needs.

[0106] Step S31: Acquire all data dimensions contained in the valid data;

[0107] Step S32: selecting at least one required data dimension from all data dimensions, and defining the priority of selecting the data dimension;

[0108] For example, you can select order information, timeliness requirements, and carrier information as the selected data dimensions, and define the priorities of the selected data dimensions from high to low as timeliness requirements, order information, and carrier information.

[0109] Step S33: Generate a scheduling rule according to the priority of the selected data dimension;

[0110] Furthermore, in step S32, the data dimension with the highest priority is the timeliness requirement. In this embodiment, the timeliness requirements include two directions: transportation timeliness and return order timeliness. The transportation timeliness is taken as the direction with the highest priority in this data dimension, and the priority is further divided according to different data levels in this direction. The reference priority can be divided from high to low into same-day delivery, next-day delivery, and third-day delivery, and then the priority of the return order timeliness is confirmed, and then the priorities of different directions of order information and carrier information are defined in turn.

[0111] Specifically, for data dimensions of the same priority, the scheduling rules may include integrated scheduling, segmented scheduling, and volume-based scheduling.

[0112] Integrated scheduling means defining scheduling rules according to the integration result in step S22, so as to realize scheduling. For example, the scheduling rules may be orders with customer information belonging to the same pickup city and the same pickup time, orders with customer information belonging to the same delivery address and the same pickup time, orders with customer information belonging to the same customer and the same delivery time, etc. These scheduling rules can be realized and integrated scheduling can be performed;

[0113] Split-segment scheduling is generally used to save transportation costs. The same order is split into multiple segments, and then scheduled after multiple sub-orders are integrated. For example, an order is split into a pickup segment, a trunk transportation segment, and a terminal delivery segment, and then separate orders are integrated in each segment. Therefore, split-segment scheduling can define scheduling rules as follows: split the same order into multiple segments, define order integration rules for each segment, and thus implement split-segment scheduling of orders that are split first and then integrated.

[0114] Split-volume scheduling is generally used to improve the loading rate. The same order is split and transported using multiple means of transportation. Data dimensions can also be selected according to actual requirements, and relevant scheduling rules can be defined based on the data dimensions to achieve split-volume scheduling.

[0115] Step S34: Based on the scheduling rules, process the valid data to obtain the available scheduling solutions;

[0116] According to the defined data dimension priorities and priorities in different directions of the data dimensions, the valid data is processed to obtain available scheduling plans. For example, based on step S34, a scheduling plan with the shortest time limit can be obtained. When the time limits are consistent, scheduling plans in different directions such as customer information, project, cargo type, pick-up time, and delivery time can be further obtained.

[0117] In actual applications, the same dispatch rule may have multiple carriers / drivers that meet the dispatch priority. You can further define the carriers or drivers specified for specific customers or routes, match the corresponding carriers / drivers according to the obtained dispatch rules, and adjust the dispatch plan based on the above content.

[0118] Step S35: Establish a dispatch rule base, and store the dispatch rules defined each time in the dispatch rule base.

[0119] Establish a dispatch rule library to store the dispatch rules defined each time. When you need to use the dispatch rules in the future, you can search for existing dispatch rules in the dispatch rule library by selecting the data dimension priority, such as timeliness priority, price priority, etc.

[0120] Step S4: Execute the scheduling scheme.

[0121] Step S5: Obtain the execution status of the scheduling scheme during execution, and adjust the scheduling scheme according to the execution status.

[0122] The execution results of the scheduling plan are scored to judge the practicality of the scheduling rules, and the scheduling rules are adjusted and stored in the scheduling rule database.

[0123] Step S6: Based on the defined scheduling rules and scheduling rule library, a supply chain intelligent scheduling model is constructed through artificial intelligence algorithms.

[0124] Specifically, the real-time data of the supply chain is used as the input variable of the supply chain intelligent scheduling model, and the real-time data is processed by the methods in steps S2 and S3 to obtain a scheduling plan, that is, the scheduling plan is used as the output variable of the supply chain intelligent scheduling model.

[0125] Furthermore, in addition to using real-time data as the input variable of the supply chain intelligent scheduling model, the data dimension priority can also be used as an input variable, so that customers can define the priority data dimension according to their needs, reduce the amount of data that needs to be processed by the supply chain intelligent scheduling model, and improve data processing efficiency.

[0126] In addition, in addition to storing the scheduling rules defined each time and the adjusted scheduling rules into the scheduling rule library to indirectly optimize the supply chain intelligent scheduling model, historical data and scheduling plans obtained based on the historical data can also be obtained, and the acquired historical data and scheduling plans are divided into training sets, test sets and verification sets. The supply chain intelligent scheduling model is trained with the training set, and the output results of the supply chain intelligent scheduling model are verified with the verification set, that is, the scheduling plan obtained after training the training set is compared with the actual scheduling plan in history, and the supply chain intelligent scheduling model is optimized according to the comparison results; finally, the supply chain intelligent scheduling model is adjusted through the test set.

[0127] On the basis of the first embodiment, this embodiment establishes a scheduling rule base to store the scheduling rules defined each time. When the same scheduling rules need to be used to process valid data in the future, the existing scheduling rules can be directly selected from the scheduling rule base, and the valid data can be processed according to the existing scheduling rules to generate optional scheduling schemes, thereby improving the efficiency of obtaining scheduling schemes and further improving the efficiency of scheduling. At the same time, before the scheduling rules are stored in the scheduling rule base, the scheduling rules can be scored and adjusted according to the execution results of the scheduling schemes to improve the accuracy of the scheduling rules in the scheduling rule base. On this basis, a supply chain intelligent scheduling model is further constructed, and artificial intelligence algorithms are used for intelligent decision-making to improve the accuracy and efficiency of scheduling. It supports the access and processing of multi-source data and is easy to expand and upgrade.

[0128] Embodiment 3

[0129] like Figure 3 As shown, a supply chain intelligent scheduling system 2 includes:

[0130] A data collection module 21, used to obtain real-time data of the supply chain;

[0131] The data processing module 22 is used to pre-process the real-time data to obtain valid data;

[0132] A rule definition module 23, used to define scheduling rules;

[0133] An intelligent scheduling module 24, used to process valid data according to the scheduling rules to obtain a scheduling solution;

[0134] The scheduling execution module 25 is used to execute the scheduling scheme.

[0135] In this embodiment, the rule definition module is also used to provide a user-friendly interface, allowing users to customize scheduling rules according to actual needs to form a scheduling rule library that meets the actual needs of the enterprise.

[0136] The modules in the supply chain intelligent scheduling system are connected through efficient data transmission and sharing mechanisms. Specifically, the data acquisition module transmits the collected data to the data processing module; the data processing module analyzes the data and transmits the results to the rule definition module and the intelligent scheduling module; the intelligent scheduling module generates a scheduling plan based on the data and scheduling rules, and implements and monitors it through the execution and monitoring module; throughout the process, the various components work together to achieve full process automation from data collection to scheduling execution.

[0137] Embodiment 4

[0138] like Figure 4 As shown, a supply chain intelligent scheduling device includes:

[0139] A memory 100, used for storing computer programs;

[0140] The processor 200 is used to execute the computer program to implement the steps of the supply chain intelligent scheduling method as described in any one of Embodiment 1 and Embodiment 2.

[0141] Embodiment 5

[0142] A readable storage medium for supply chain intelligent scheduling, wherein a computer program is stored on the readable storage medium, and when the computer program is executed, the steps of the supply chain intelligent scheduling method described in Embodiment 1 and Embodiment 2 are implemented.

[0143] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0144] The present invention may be a system, method and / or computer program product. The computer program product may include a computer-readable storage medium (or medium) having computer-readable program instructions thereon, the computer-readable program instructions being used to cause a processor to perform aspects of the present invention.

[0145] The computer programs described herein are computer-readable program instructions that can be downloaded from a computer-readable storage medium to a corresponding computing / processing device or downloaded to an external computer or external storage device via a network (e.g., the Internet, a local area network, a wide area network, and / or a wireless network). The network may include copper transmission cables, optical transmission fibers, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in a computer-readable storage medium in the corresponding computing / processing device.

[0146] The computer-readable program instructions for performing the operation of the present invention can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, and conventional procedural programming languages, such as "C" programming language or similar programming languages. The computer-readable program instructions can be executed completely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or completely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any type of network (including a local area network (LAN) or a wide area network (WAN)), or can be connected to an external computer (for example, by using the Internet of an Internet service provider). In some embodiments, an electronic circuit (including, for example, a programmable logic circuit, a field programmable gate array (FPGA) or a programmable logic array (PLA)) can execute a computer-readable program instruction to personalize the electronic circuit by utilizing the state information of the computer-readable program instructions, so as to perform aspects of the present invention.

[0147] Aspects of the present invention are described herein with reference to flowcharts of methods, systems, devices, and computer program products according to embodiments of the present invention and / or block diagrams. It should be understood that each box in the flowchart and / or block diagram and the combination of boxes in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0148] These computer-readable program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine that, when executed by a processor of the computer or other programmable data processing apparatus, creates a device for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions may also be stored in a computer-readable storage medium that can instruct a computer, a programmable data processing apparatus, and / or other device to function in a particular manner, such that a computer-readable storage medium having instructions stored therein includes an article of manufacture that includes instructions for implementing various aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0149] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with the art within the technical scope disclosed in the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A supply chain intelligent scheduling method, characterized in that: The supply chain intelligent scheduling method comprises the following steps: Get real-time data on the supply chain; Preprocessing the real-time data to obtain valid data; Defining scheduling rules, processing valid data according to the scheduling rules, and obtaining a scheduling plan; The scheduling scheme is executed.

2. The supply chain intelligent scheduling method according to claim 1 is characterized in that: The obtaining of real-time data of the supply chain specifically involves obtaining real-time data from any one or more of orders, logistics providers, and carriers of the supply chain.

3. The supply chain intelligent scheduling method according to claim 1 is characterized in that: The preprocessing of the real-time data to obtain valid data comprises: Clean the real-time data and obtain all data dimensions contained in the real-time data; Based on all data dimensions, perform data integration of a single data dimension in turn; Analyze and process the integrated data to obtain valid data.

4. The supply chain intelligent scheduling method according to claim 1 is characterized in that: Defining the scheduling rules includes: Get all data dimensions contained in the valid data; Select at least one required data dimension from all data dimensions and define the priority of selecting data dimensions; Generate scheduling rules based on the priority of the selected data dimension.

5. The supply chain intelligent scheduling method according to claim 4 is characterized in that: Generating the scheduling rule according to the priority of selecting the data dimension includes: selecting data dimensions with the same priority, and selecting any one of integrated scheduling, segmented scheduling, and volume-splitting scheduling to generate a corresponding scheduling rule.

6. The supply chain intelligent scheduling method according to claim 3 is characterized in that: The processing of valid data according to the scheduling rules to obtain a scheduling solution includes: based on the scheduling rules, processing valid data to obtain an optional scheduling solution.

7. The supply chain intelligent scheduling method according to claim 1 is characterized in that: The supply chain intelligent scheduling method also includes: obtaining the execution status of the scheduling plan during execution, and adjusting the scheduling plan according to the execution status.

8. The supply chain intelligent scheduling method according to claim 1, characterized in that: The supply chain intelligent scheduling method also includes: establishing a scheduling rule base, and storing the scheduling rules defined each time through the scheduling rule base.

9. A supply chain intelligent scheduling method according to claim 8, characterized in that: The supply chain intelligent scheduling method also includes: building a supply chain intelligent scheduling model through an artificial intelligence algorithm based on defined scheduling rules and a scheduling rule library.

10. A supply chain intelligent scheduling system, characterized in that: The supply chain intelligent scheduling system includes: Data collection module, used to obtain real-time data of the supply chain; A data processing module, used for preprocessing the real-time data to obtain valid data; Rule definition module, used to define scheduling rules; An intelligent scheduling module, used to process valid data according to the scheduling rules to obtain a scheduling plan; The scheduling execution module is used to execute the scheduling plan.

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