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CN-122022745-A - Cross-border supply chain intelligent matching and collaborative management system

CN122022745ACN 122022745 ACN122022745 ACN 122022745ACN-122022745-A

Abstract

The invention discloses an intelligent matching and collaborative management system of a cross-border supply chain, and relates to the technical field of cross-border supply chain management. The system comprises a matching parameter acquisition module, a matching dimension adjustment module and a supply chain matching module, wherein the matching parameter acquisition module acquires demand data of a demand side and supply data of each supply side, dynamically acquires a first dimension matching parameter and a second dimension matching parameter of each cross-border supply chain based on the demand data and the supply data of the supply side, the matching dimension adjustment module executes matching dimension dynamic adjustment based on transportation strategy driving parameters in the demand data, and the supply chain matching module carries out first dimension matching and second dimension matching according to the first dimension matching parameter and the second dimension matching parameter of each cross-border supply chain respectively, and screens based on a matching dimension weight dynamic adjustment result and a dimension matching result of each matching supply chain to obtain a final cross-border supply chain.

Inventors

  • XIA YU

Assignees

  • 企发丝路(北京)科技发展有限公司

Dates

Publication Date
20260512
Application Date
20260119

Claims (10)

  1. 1. The intelligent matching and collaborative management system for the cross-border supply chain is characterized by comprising a matching parameter acquisition module, a matching dimension adjustment module and a supply chain matching module: The matching parameter acquisition module is used for acquiring the demand data of the demand side and the supply data of each supply side, and dynamically acquiring a first dimension matching parameter and a second dimension matching parameter of each cross-border supply chain based on the demand data and the supply data of the supply side, wherein each cross-border supply chain is an independent supply link constructed by the demand side and each supply side based on a point-to-point corresponding relation, the first dimension matching represents the static degree of the key node of cross-border product transportation, and the second dimension matching parameter represents the dynamic degree of the key node of cross-border product transportation; The matching dimension adjustment module is used for executing matching dimension dynamic adjustment based on transportation strategy driving parameters in the demand data, the matching dimension dynamic adjustment represents the allocation proportion of dynamic adjustment dimension weight parameters so as to adapt to different bias weights of transportation static and dynamic efficiency under different demand scenes, and the dimension weight parameters comprise a first dimension weight and a second dimension weight; The supply chain matching module is used for carrying out first dimension matching according to first dimension matching parameters of each cross-border supply chain, outputting each to-be-selected matching supply chain, carrying out second dimension matching on the to-be-selected matching supply chain based on second dimension matching parameters, outputting each matching supply chain, and screening and obtaining a final cross-border supply chain based on a matching dimension weight dynamic adjustment result and a dimension matching result of each matching supply chain, wherein the dimension matching result comprises a first dimension matching result and a second dimension matching result.
  2. 2. The cross-border supply chain intelligent matching and collaborative management system according to claim 1, wherein the step of dynamically obtaining first dimension matching parameters and second dimension matching parameters for each cross-border supply chain based on the demand data and supply data on a supply side comprises: Obtaining target basic parameters of a demand side based on the demand data, wherein the target basic parameters comprise, but are not limited to, basic attributes of demand goods, target storage locations, target transportation destinations, target cost intervals, target aging requirements and order priority identifiers; performing primary screening on each supply side based on the target basic parameters to obtain each candidate supply side; Performing point-to-point association on each candidate supply side and the demand side to generate a corresponding cross-border supply chain; Extracting corresponding key node network data of each cross-border supply chain, and calculating and generating first dimension matching parameters based on the key node network data, wherein the first dimension matching parameters comprise network depth matching degree, position matching degree of each key node and average path matching degree of each key node; and extracting corresponding key node circulation data of each cross-border supply chain, and calculating and generating second dimension matching parameters based on the key node circulation data, wherein the second dimension matching parameters comprise transportation timeliness matching degree, node connection matching degree and node cooperation matching degree of each key node.
  3. 3. The cross-border supply chain intelligent matching and collaborative management system according to claim 1, wherein the transportation policy driven parameters include transportation data granularity, transportation data update frequency, and collaborative demand strength; the step of performing matching dimension dynamic adjustment based on the transportation policy driven parameters in the demand data comprises: acquiring preset dimension weight reference parameters, wherein the dimension weight reference parameters comprise a first dimension reference coefficient and a second dimension weight reference coefficient; Performing comparison influence operation on the transportation strategy driving parameters and preset transportation strategy driving reference parameters respectively, and performing weighting coupling treatment on comparison influence operation results by using preset transportation strategy weight parameters respectively to obtain transportation strategy driving influence parameters, wherein the transportation strategy driving reference parameters comprise granularity reference values, update frequency reference values and cooperative intensity reference values, and the transportation strategy weight parameters comprise granularity influence coefficients, update frequency influence coefficients and cooperative intensity influence coefficients; Inquiring a preset weight coefficient adjustment relation table according to the transportation strategy driving influence parameters to obtain corresponding weight coefficient adjustment proportions, wherein the weight coefficient adjustment relation table defines the mapping relation between the transportation strategy driving influence parameters in different ranges and the corresponding weight coefficient adjustment amounts; processing the second dimension weight reference coefficient by utilizing the weight coefficient adjustment proportion to obtain a second dimension basic coefficient, and coupling the second dimension basic coefficient with the first dimension reference coefficient to obtain a comprehensive matching basic coefficient; and respectively calculating the ratio of the first dimension reference coefficient to the second dimension basic coefficient to the comprehensive matching basic coefficient to obtain an adjusted first dimension weight and an adjusted second dimension weight.
  4. 4. The intelligent matching and collaborative management system of cross-border supply chains according to claim 1, wherein the step of performing a first dimension matching based on a first dimension matching parameter of each cross-border supply chain and outputting each candidate matching supply chain comprises: Performing comparison influence operation on first dimension matching parameters of each cross-border supply chain and preset first dimension matching reference parameters respectively, and performing weighting coupling treatment on comparison influence operation results by using preset first dimension weight parameters respectively to obtain first dimension matching parameters of each cross-border supply chain, wherein the first dimension matching reference parameters comprise network depth matching degree reference quantity, position matching degree reference quantity and path matching degree reference quantity, and the first dimension weight parameters comprise network depth matching degree influence coefficient, position matching degree influence coefficient and path matching degree influence coefficient; Comparing the first dimension matching parameters of each cross-border supply chain with a preset first dimension matching threshold, marking the cross-border supply chain as a to-be-judged matching supply chain if the first dimension matching parameters of any cross-border supply chain are lower than the first dimension matching threshold, and carrying out first dimension matching based on the replacement nodes corresponding to each key node of the to-be-judged matching supply chain, and screening to obtain a to-be-selected matching supply chain and a non-to-be-selected matching supply chain; If the first dimension matching parameter of any cross-border supply chain is not lower than the first dimension matching threshold, marking the cross-border supply chain as a supply chain to be matched; and counting and outputting each candidate matching supply chain.
  5. 5. The cross-border supply chain intelligent matching and collaborative management system according to claim 4, wherein the step of performing a first dimension matching based on replacement nodes corresponding to key nodes of the supply chain to be determined to match comprises: If the position matching degree of any key node of the supply chain to be judged is lower than the position matching degree reference quantity, acquiring a replacement node corresponding to the key node; If yes, judging whether the average path matching degree of the related paths of the replacement nodes reaches the path matching degree reference quantity, if yes, replacing the key stage with the replacement nodes, and if not, carrying out additional processing; And re-executing the first dimension matching based on the first dimension matching parameters of the to-be-determined matching supply chains after replacement, generating first dimension matching parameters of the to-be-determined matching supply chains after replacement, marking as a to-be-selected matching supply chain if the first dimension matching parameters of the to-be-determined matching supply chains after any replacement are not lower than the first dimension matching parameters, and marking as a non-to-be-selected matching supply chain if the first dimension matching parameters of the to-be-determined matching supply chains after any replacement are still lower than the first dimension matching parameters.
  6. 6. The cross-border supply chain intelligent matching and collaborative management system according to claim 1, wherein the step of performing second dimension matching on the candidate matching supply chains based on second dimension matching parameters and outputting each matching supply chain comprises: Performing comparison influence operation on second dimension matching parameters of each to-be-selected matching supply chain and preset second dimension matching reference parameters respectively, and performing weighting coupling treatment on comparison influence operation results by using preset second dimension weight parameters respectively to obtain second dimension matching parameters of each to-be-selected matching supply chain, wherein the second dimension matching reference parameters comprise a transportation aging matching degree reference quantity, a node connection matching degree reference quantity and a node cooperative matching degree reference quantity, and the second dimension weight parameters comprise a transportation aging matching degree influence coefficient, a node connection matching degree influence coefficient and a node cooperative matching degree influence coefficient; Comparing the second dimension matching parameters of the to-be-selected matching supply chains with a preset second dimension matching threshold value respectively, marking as a non-matching supply chain if the second dimension matching parameter of any one of the to-be-selected matching supply chains is lower than the second dimension matching parameter, and marking as a matching supply chain if the second dimension matching parameter of any one of the to-be-selected matching supply chains is not lower than the second dimension matching parameter; each matching supply chain is counted and output.
  7. 7. The cross-border supply chain intelligent matching and collaborative management system according to claim 1, wherein the step of screening the final cross-border supply chain based on matching dimension weight dynamic adjustment results and dimension matching results of each matching supply chain comprises: respectively carrying out weighting coupling treatment on the first dimension matching parameters and the second dimension matching parameters of each matching supply chain based on the adjusted dimension weight parameters to obtain comprehensive matching parameters of each matching supply chain; according to the comprehensive matching parameters, sequencing all the matching supply chains in a reverse order, and marking the first matching supply chain as a cross-border supply chain to be judged; Comparing the comprehensive matching parameters of the cross-border supply chain to be judged with a preset comprehensive matching threshold, outputting a matching abnormality prompt if the comprehensive matching parameters of the cross-border supply chain to be judged are lower than the comprehensive matching threshold, executing an adaptive parameter relaxation adjustment mechanism based on matching failure attribution, and marking the cross-border supply chain to be judged as a final cross-border supply chain if the comprehensive matching parameters of the cross-border supply chain to be judged are not lower than the comprehensive matching threshold.
  8. 8. The cross-border supply chain intelligent matching and collaborative management system according to claim 7, wherein the executing the adaptive parameter relaxation adjustment mechanism based on matching failure attribution comprises: Acquiring a history matching task set triggering the abnormal matching prompt in a preset statistical period, and calculating the matching failure rate of the history matching task set; if the matching failure rate is greater than or equal to a preset failure rate early warning threshold value, triggering parameter relaxation adjustment; respectively counting average differences between a first dimension matching parameter and a first dimension matching threshold value of each cross-border supply chain to be judged in the history matching task set, and marking the average differences as a static deviation average value and average differences between a second dimension matching parameter and a second dimension matching threshold value as a dynamic deviation average value; according to the static deviation average value and the dynamic deviation average value, carrying out cooperative relaxation adjustment on the first dimension matching reference parameter and the second dimension matching reference parameter: if the static deviation average value is greater than or equal to the dynamic deviation average value, respectively downwards regulating the network depth matching degree reference quantity, the position matching degree reference quantity and the path matching degree reference quantity in the first dimension matching reference parameter to corresponding relaxation lower limit values; if the static deviation average value is smaller than the dynamic deviation average value, respectively downwards regulating the transportation timeliness matching degree reference quantity, the node engagement matching degree reference quantity and the node cooperation matching degree reference quantity in the second dimension matching reference parameter to corresponding relaxation lower limit values; And after the reference parameters are adjusted downwards, re-executing the supply chain matching process aiming at the current demand data based on the updated matching reference parameters.
  9. 9. A computing device, comprising: one or more processors; storage means for storing one or more programs that when executed by the one or more processors cause the one or more processors to implement the system of any of claims 1-8.
  10. 10. A computer readable storage medium, characterized in that it stores a computer program or instructions that, when executed, cause the system according to any one of claims 1 to 8 to be executed.

Description

Cross-border supply chain intelligent matching and collaborative management system Technical Field The invention relates to the technical field of cross-border supply chain management, in particular to an intelligent matching and collaborative management system of a cross-border supply chain. Background The cross-border supply chain is supported by taking digitization as a core, key technologies such as block chain, internet of things, big data, artificial intelligence, cloud computing and the like are integrated, and a digital twin, electronic customs and international trade single window system are assisted, so that a full-chain efficient collaborative system is constructed. The block chain guarantees that commodity tracing and data cannot be tampered, the Internet of things realizes real-time monitoring of cargo positions and environments, big data and AI (advanced information technology) optimization demand prediction, inventory management and logistics path planning, cloud computing provides cross-main-body data sharing and elastic computing force support, digital twinning optimizes physical supply chain operation through virtual simulation, a single window system breaks through multi-department data barriers, and the clearance efficiency is greatly improved. The technologies cooperate to exert force, break the island of region and information, realize the closed loop intercommunication of information flow, logistics and fund flow, not only enhance the transparency, toughness and compliance of the supply chain, but also effectively reduce the operation cost, shorten the delivery period, and adapt to the dual requirements of full spheroidization and regional layout. The existing cross-border supply chain collaborative management method mainly relies on a cross-border supply chain collaborative platform as a carrier, integrates the technologies of big data, artificial intelligence, blockchain, internet of things and the like, acquires multi-dimensional data such as order demands, capacity resources, storage capacity, clearance policies, logistics timeliness and the like of both supply and demand parties, utilizes an AI algorithm to realize intelligent matching of goods sources, capacity and storage resources, simultaneously builds a reliable data sharing system by means of the blockchain technology, opens up information barriers among multiple main bodies such as suppliers, logistics service providers, customs and distributors, realizes the collaborative linkage of all flows such as order placement, logistics scheduling, clearance reporting, inventory management, fund settlement and the like, assists with real-time monitoring and dynamic optimization mechanisms, timely adjusts matching strategies and collaborative schemes, and finally achieves the aim of optimizing resource allocation of each link of the cross-border supply chain and realizing efficient flow operation. A cross-border supply chain data management system and method disclosed in the patent application with publication number of CN118780733B comprises the steps of identifying all relevant nodes in a cross-border supply chain as data sources, extracting all the data sources based on a set acquisition period to obtain a multi-dimensional data set of the cross-border supply chain, carrying out data preprocessing on the multi-dimensional data set of the cross-border supply chain, taking the inventory level which minimizes the total cost and maintains a set standard as an optimization target, defining a first constraint condition, a second constraint condition and a third constraint condition, calculating the multi-dimensional data set of the cross-border supply chain through ASGD algorithm, solving the optimal order point and the optimal order quantity, and generating a future inventory level prediction result according to the optimal order point and the optimal order quantity. The system and the method for managing the supply chain for cross-border trade disclosed in the CN119809072A patent application comprise a blockchain network, a compliance code generation module, a data acquisition module, a route optimization module and a user interface module, wherein the blockchain network is used for storing and managing all data related to the supply chain, the compliance code generation module is used for generating unique product codes according to the product type and product information of each product and generating a compliance number of each region based on the compliance condition of each region which is met by the current product, the data acquisition module is used for acquiring logistics state and environment data in real time through a sensor and an IoT device and uploading the data to the blockchain network, the route optimization module is used for calculating an optimal logistics route by using a dynamic optimization algorithm based on the compliance codes and real-time data analysis, and the user interface module is used for providing