Supply chain management system and method for cross-border trade

Abstract

The invention discloses a supply chain management system and method for cross-border trade, and the system comprises a block chain network which is used for storing and managing all data related to a supply chain, a compliance code generation module which is used for generating a unique product code according to the product type and product information of each product, and a supply chain management module which is used for storing and managing all data related to the supply chain. Generating a compliance number of each region on the basis of compliance conditions of each region which the current product conforms to; the data acquisition module is used for acquiring logistics state and environment data in real time through a sensor and IoT (Internet of Things) equipment and uploading the data to a block chain network; the route optimization module is used for calculating an optimal logistics route by using a dynamic optimization algorithm based on compliance coding and real-time data analysis; the user interface module is used for providing a user interface for a participant to carry out information query and operation; according to the supply chain management system and method for the cross-border trade, multiple technical problems of compliance management, logistics optimization, data transparency, information sharing and the like in the cross-border trade are solved.

Description

Technical Field

[0001] The present invention relates to a supply chain management system and method for cross-border trade. Background Art

[0002] With the development of the global economy, cross-border trade has become an important part of international trade. Cross-border trade not only involves the exchange of products between multiple countries or regions, but also requires solving complex issues such as compliance, logistics, and information transparency between different regions. Therefore, how to effectively manage cross-border supply chains, ensure product compliance, improve logistics efficiency, and reduce supply chain management costs has become a technical problem that governments, enterprises, and logistics service providers need to solve urgently.

[0003] In traditional cross-border trade, products need to comply with the regulations and standards of different countries or regions, especially in the field of sensitive products such as food, medicine, chemicals, etc. The compliance requirements of each region are different, and in the supervision process, the acquisition and verification of compliance information are often delayed or inaccurate. Existing supply chain management systems usually rely on manual operations in terms of compliance management, lack effective automation and real-time monitoring mechanisms, resulting in difficulty in real-time updating of compliance information and prone to compliance risks in cross-border trade.

[0004] In addition, due to the ever-changing compliance standards of different countries or regions, companies often need to conduct complex compliance reviews and adjustments for different markets when dealing with cross-border trade. The existing system has large data management and update costs when generating and tracking product compliance information, which directly affects the efficiency and risk management capabilities of cross-border trade.

[0005] Traditional supply chain management systems usually rely on centralized data storage and management methods, which makes data vulnerable to tampering, loss or misuse. In many links of the supply chain, the data flow between various participants (such as suppliers, manufacturers, logistics companies, etc.) is usually not transparent enough, resulting in information asymmetry, which in turn affects the trust in cross-border trade.

[0006] In actual operations, different participants often rely on paper documents or isolated electronic data systems to track and verify the same product, resulting in untimely information transmission, poor data accuracy, and even data tampering. This makes the transparency of the supply chain, the reliability and traceability of data important factors restricting the efficiency and security of cross-border trade.

[0007] Cross-border logistics is one of the key factors affecting the efficiency and cost of cross-border trade. In traditional supply chain management, logistics information can often only be tracked through static manual recording and updating, lacking a real-time dynamic monitoring mechanism. Since cross-border logistics routes often cross multiple countries and regions, and are affected by different geographical, environmental, traffic, weather and other factors, delays or other unforeseen risks may occur during transportation.

[0008] Existing logistics management systems usually have difficulty in obtaining logistics status and environmental data in real time, and lack the ability to dynamically optimize for complex situations. Traditional logistics optimization usually relies only on static data analysis and cannot be adjusted in time according to real-time changing environments and compliance requirements, resulting in high logistics costs, low transportation efficiency, and even non-compliance with compliance requirements in certain regions.

[0009] The supply chain of cross-border trade usually involves multiple links and different participants, including manufacturers, suppliers, warehousing companies, logistics companies, customs and final consumers. In such a complex ecosystem, information flow and coordination are particularly important. However, in the existing cross-border supply chain management system, information transmission usually relies on a single, limited channel, resulting in poor information flow and a lack of effective communication and coordination mechanisms between participants.

[0010] Traditional supply chain systems often isolate the operations of various parties, and data sharing and collaboration capabilities are weak. The lack of standardized data interfaces between the systems of different participants makes information updating and sharing inefficient. Especially in cross-border trade, since multiple countries or regions are involved, cross-system, cross-cultural and cross-language information collaborative management is more difficult, which greatly increases the complexity and risk of supply chain management.

[0011] Existing supply chain management systems lack sufficiently intelligent dynamic optimization capabilities. In complex cross-border logistics, how to balance compliance requirements, transportation costs, transportation time and other factors is always a challenge. Traditional logistics optimization methods mostly rely on static models and rules, ignoring the dynamic impact of actual environmental changes and real-time data, and are unable to adjust optimization strategies in a timely manner.

[0012] Due to the lack of real-time data support and dynamic adjustment mechanisms, many traditional systems are unable to respond and adjust quickly when faced with complex and dynamic cross-border supply chains, resulting in increased logistics costs, delayed transportation time, and even compliance risks, which in turn affects the smooth progress of cross-border trade. Summary of the invention

[0013] The purpose of the present invention is to provide a supply chain management system for cross-border trade, which ensures the transparency and immutability of data through blockchain technology, and combines modules such as compliance code generation, real-time data collection, and dynamic route optimization to solve multiple technical problems in cross-border trade, such as compliance management, logistics optimization, data transparency, and information sharing. It greatly improves the efficiency, reliability, and compliance of the cross-border supply chain, while reducing the risks caused by compliance issues and improper logistics.

[0014] The technical solution adopted by the present invention to solve its technical problem is:

[0015] A supply chain management system for cross-border trade, including:

[0016] A blockchain network to store and manage all data related to the supply chain and ensure data immutability and transparency;

[0017] A compliance code generation module, used to generate a unique product code according to the product type and product information of each product, and generate a compliance number for each region based on the compliance conditions of each region that the current product complies with. If the product meets the compliance requirements of a region, a compliance number is generated for the region, otherwise no compliance number is generated. The compliance number is composed of multiple regional compliance numbers;

[0018] The data collection module collects logistics status and environmental data in real time through sensors and IoT devices, and uploads the data to the blockchain network;

[0019] Route optimization module, based on compliance coding and real-time data analysis, uses dynamic optimization algorithms to calculate the optimal logistics route, ensuring that the product's logistics route only passes through areas that meet compliance requirements;

[0020] The user interface module provides a user interface for participants to query and operate information.

[0021] Preferably, participants in the blockchain network include manufacturers, suppliers, logistics companies and customs, and each participant can access and update product-related data in real time.

[0022] Preferably, the system further comprises an early warning module for issuing a warning and prompting to adjust the route when the system detects non-compliant areas in the logistics route.

[0023] Another technical problem to be solved by the present invention is to provide a supply chain management method for cross-border trade, comprising the following steps:

[0024] Obtain compliance codes for products;

[0025] Analyze the areas that meet the compliance standards based on the compliance codes;

[0026] Collect real-time logistics data, including traffic conditions, weather conditions, and checkpoint traffic conditions;

[0027] Use dynamic optimization algorithms to calculate the optimal logistics route;

[0028] Select the best route in the compliance areas and ensure that the selected logistics route only passes through areas that meet the compliance standards;

[0029] Dynamically adjust selected routes based on real-time data to ensure transportation paths always meet compliance standards.

[0030] As a preferred method, the method of obtaining the compliance code of the product is:

[0031] Extract basic product information from the supply chain management system and automatically import it, including product name, model, specification, production location, raw materials, and production process.

[0032] Based on the basic information of the product, query the pre-established compliance standards database, which includes the compliance requirements of products in different regions, countries, and industries;

[0033] Compliance standards include quality certification, environmental protection requirements, safety standards, and import and export regulations;

[0034] Classify products into relevant compliance standard categories based on product type and purpose;

[0035] Generate a unique compliance code based on preset rules and product compliance requirements. The code includes: product industry code, applicable regulations, applicable country code, and version number;

[0036] After obtaining the compliance code, verification is performed to ensure that the product compliance code is consistent with the actual compliance requirements.

[0037] As a preferred method, the method of analyzing the regions meeting the compliance standards according to the compliance codes is:

[0038] Decode compliance codes and identify region-specific information.

[0039] Use the compliance standards database to query the regional regulations corresponding to the code;

[0040] Combine certification marks and regulatory requirements to determine applicable markets and regions.

[0041] As a preferred method, the method of calculating the optimal logistics route using a dynamic optimization algorithm is:

[0042] Initialize the pheromone value for each path, and set the initial pheromone value of all paths to be the same;

[0043] Set according to the initial quality of the path;

[0044] Each ant chooses the path to take next based on probability. The selection probability formula is as follows:

[0045]

[0046] Where Pij is the probability of an ant choosing from node i to node j, τij is the pheromone concentration on the path (i, j), ηij is the heuristic function, α and β are the influencing factors of the pheromone and the heuristic function respectively, and J is the set of selectable paths. Ants complete the path planning of a delivery by selecting a path until all ants complete a round of path search;

[0047] The pheromones on all paths will evaporate at a certain ratio, which can be expressed as:

[0048] τ ij =(1-ρ)·τ ij

[0049] Among them, ρ is the pheromone evaporation rate, τij is the pheromone concentration on path (i, j);

[0050] After each round of iteration, the pheromones on the path are updated based on the quality of the ants’ path;

[0051] τ ij =τ ij +Δτ ij

[0052] Among them, Δτij is the amount of pheromone added on each path, which is inversely proportional to the quality of the path;

[0053]

[0054] Among them, Q is a constant and L is the total cost;

[0055] After each round of ant search, the best path in the current search is recorded and the global optimal solution is updated;

[0056] When the preset maximum number of iterations is reached or the preset convergence condition is met, the algorithm stops.

[0057] As a preferred method, the best route is selected in the compliant areas to ensure that the selected logistics route only passes through areas that meet the compliance standards:

[0058] During the path selection process, ensure that the selected logistics routes only pass through areas that meet the compliance standards, and eliminate any paths that include areas that do not meet the compliance standards.

[0059] Another technical problem to be solved by the present invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the supply chain management method for cross-border trade as described above is implemented.

[0060] Another technical problem to be solved by the present invention is to provide a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the supply chain management method for cross-border trade as described above is implemented.

[0061] The beneficial effects of the present invention are:

[0062] Through the compliance code generation module, the system generates compliance numbers that meet the compliance requirements of each region based on the type and information of each product, and ensures that only regions that meet the compliance standards will generate corresponding compliance numbers. This ensures that products strictly comply with the compliance requirements of various countries or regions during cross-border trade, avoiding trade risks or delays caused by compliance issues; by using the blockchain network, the system can ensure that all supply chain-related data (such as logistics status, compliance information, environmental data, etc.) are stored and managed in an unalterable and transparent manner. The data transparency and unalterability provided by the blockchain can enhance the trust of all parties in supply chain data, thereby improving the security and efficiency of cross-border trade.

[0063] The data collection module collects logistics status and environmental data in real time through sensors and IoT devices, and uploads it to the blockchain network to ensure the timeliness and accuracy of the information. At the same time, the route optimization module uses a dynamic optimization algorithm to calculate the optimal logistics route based on real-time collected data and compliance codes to ensure that the logistics path only passes through areas that meet compliance requirements. This can improve logistics efficiency and reliability while ensuring compliance; through the user interface module, an information query and operation platform is provided for all participants. Whether it is suppliers, logistics companies or other stakeholders, they can query the compliance status, logistics information, environmental data and optimal route of the product in real time through the user interface, thereby improving the collaborative efficiency of the supply chain and reducing problems caused by information asymmetry.

[0064] The route optimization module combines compliance coding and real-time data, uses a dynamic optimization algorithm to calculate the logistics route, and considers compliance requirements, transportation costs, transportation time and other factors in each region to find the best logistics route. By dynamically adjusting the optimization strategy, it can cope with various complex supply chain challenges, thereby improving the overall efficiency of the supply chain. Specific implementation methods

[0066] The principles and features of the present invention are described below, and the examples are only used to explain the present invention and are not used to limit the scope of the present invention. The present invention is described more specifically by way of example in the following paragraphs. According to the following description and claims, the advantages and features of the present invention will become clearer.

[0067] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items. Example

[0068] A supply chain management system for cross-border trade, including:

[0069] A blockchain network to store and manage all data related to the supply chain and ensure data immutability and transparency;

[0070] A compliance code generation module, used to generate a unique product code according to the product type and product information of each product, and generate a compliance number for each region based on the compliance conditions of each region that the current product complies with. If the product meets the compliance requirements of a region, a compliance number is generated for the region, otherwise no compliance number is generated. The compliance number is composed of multiple regional compliance numbers;

[0071] The data collection module collects logistics status and environmental data in real time through sensors and IoT devices, and uploads the data to the blockchain network;

[0072] Route optimization module, based on compliance coding and real-time data analysis, uses dynamic optimization algorithms to calculate the optimal logistics route, ensuring that the product's logistics route only passes through areas that meet compliance requirements;

[0073] The user interface module provides a user interface for participants to query and operate information.

[0074] Blockchain technology ensures that all stored supply chain data cannot be tampered with or deleted after creation, providing a high degree of credibility. This is particularly important for compliance reviews in cross-border trade, as it can avoid forging or tampering with compliance information; all transaction, logistics and compliance-related data will be recorded on the blockchain and all supply chain participants can access it at any time. This transparency helps to enhance the trust of all parties in the supply chain, especially when it involves multiple countries and regions, and can effectively avoid information asymmetry.

[0075] The compliance code generation module automatically generates numbers that meet the compliance requirements of different regions based on the type and information of the product. This process ensures that compliance checks in each region can be conducted efficiently and automatically, reducing the risk of manual intervention and errors; only products that meet the compliance requirements of a specific region will generate corresponding compliance numbers, and non-compliant products cannot enter certain regions through the system, thereby reducing compliance risks in cross-border trade; the compliance number is composed of compliance numbers of multiple regions to ensure that multiple compliance requirements around the world are met. Through a unified coding system, users can easily view the multi-country compliance information of products and improve the efficiency of compliance management.

[0076] Through sensors and IoT devices, the system can collect logistics status and environmental data (such as temperature and humidity, transportation progress, transportation routes, etc.) in real time. These data are directly uploaded to the blockchain network to ensure the timeliness and accuracy of the information; traditional logistics management often relies on manual records or static data, and the system avoids human errors and delays through real-time data collection, ensuring timely updates and high accuracy of data; the system can make adjustments based on real-time environmental data, which is particularly suitable for dealing with unforeseen external factors (such as weather, traffic, emergencies, etc.), improving the adaptability and flexibility of cross-border logistics.

[0077] The route optimization module uses a dynamic optimization algorithm to calculate the optimal logistics route based on compliance coding and real-time logistics data. This means that the system can adjust the logistics route in real time according to actual conditions (such as logistics progress, weather conditions, traffic conditions, etc.) to ensure smooth transportation and compliance requirements; by considering compliance conditions and real-time data, the system can ensure that products always choose to pass through areas that meet the requirements, avoid taking routes that do not comply with regulations, and reduce transportation delays and additional costs caused by compliance issues; the optimized route not only reduces transportation time and cost, but also avoids unnecessary cumbersome procedures during cross-border transportation, greatly improving the overall efficiency of cross-border trade.

[0078] The user interface module provided enables all participants in the supply chain (such as suppliers, logistics companies, customs, end consumers, etc.) to easily query and operate. Whether it is querying compliance information, real-time logistics status, or performing operation instructions, the user interface provides an intuitive and convenient operation experience; users can obtain the required information through a unified platform, reducing the complexity of operating across multiple systems or platforms. The transparent interface design enables participants to clearly see the progress of each link, improving the transparency and collaboration efficiency of the entire supply chain.

[0079] The system not only focuses on compliance, but also integrates compliance management with logistics status in real time to ensure that every link in cross-border trade can meet compliance and efficiency requirements at the same time; automated compliance code generation, logistics data collection and route optimization functions greatly reduce human intervention, reduce human errors and operational complexity, and reduce bottlenecks in the process; because the system can track all relevant data (including compliance information and logistics status) in real time, supply chain participants in different countries or regions can collaborate more efficiently, further improving the collaborative efficiency of cross-border supply chains.

[0080] Participants in the blockchain network include manufacturers, suppliers, logistics companies and customs, and each participant can access and update product-related data in real time; the system further includes an early warning module for issuing warnings and prompting route adjustments when the system detects non-compliant areas in the logistics route.

[0081] The blockchain network ensures that all participants (producers, suppliers, logistics companies and customs) can access all data related to the product in real time. This data sharing eliminates information silos, allowing participants in all links to see unified and authentic data, and improving trust in cross-border trade; due to the immutability of the blockchain, all transaction records and logistics data cannot be changed or deleted once uploaded to the blockchain. This means that every participant can rely on real historical records to make decisions, avoiding the risk of falsified data or improper operations, which is especially important for compliance inspections and customs reviews.

[0082] Each participant can access compliance-related information in real time, such as the product's compliance code, compliance number, and related certification data. This allows each link in the supply chain to clearly know whether the current product meets the compliance requirements of a specific region, ensuring that compliance will not be ignored or omitted; since the generation of compliance codes and compliance numbers is based on the real-time compliance data of the product, if there are any changes to regulations or new requirements in any region, the data on the blockchain can be updated immediately, and all relevant parties can obtain information in real time, avoiding compliance issues.

[0083] The early warning module can detect in time whether the product passes through areas that do not meet compliance requirements during transportation by monitoring the logistics path in real time. If the logistics path is found to enter a non-compliant area, the system will automatically issue a warning and prompt to adjust the route to help participants avoid non-compliance. This early warning function can effectively reduce the risk of delays, fines or detentions caused by non-compliant paths, ensuring that products can reach their destination smoothly and on time. This is crucial for compliance requirements and customs inspections in cross-border trade, reducing the occurrence of human errors and delays. Unlike traditional post-inspections, the system can achieve pre-intervention and timely adjust logistics routes to avoid the expansion or complication of problems.

[0084] By real-time monitoring of compliance paths and real-time data updates, the system can dynamically adjust logistics routes to ensure that logistics routes not only meet compliance requirements but are also more efficient. Re-examination or delays caused by non-compliant paths are avoided, reducing waste of time and costs; the system can automatically detect the compliance of logistics paths and make adjustments, reducing manual intervention and operational errors, making the entire supply chain process smoother. The early warning module provides an automatic adjustment plan to avoid delays caused by manual judgment or negligence.

[0085] Manufacturers, suppliers, logistics companies, customs and other parties can share data and collaborate in real time through the blockchain platform. Each participant can keep abreast of the information of other links, making the coordination of cross-border supply chains smoother; when the regulations, routes, customs policies, etc. involved in cross-border trade change, all parties can quickly receive early warnings and respond, reducing delays and errors caused by information asymmetry.

[0086] A supply chain management method for cross-border trade, comprising the following steps:

[0087] Obtain compliance codes for products;

[0088] Analyze the areas that meet the compliance standards based on the compliance codes;

[0089] Collect real-time logistics data, including traffic conditions, weather conditions, and checkpoint traffic conditions;

[0090] Use dynamic optimization algorithms to calculate the optimal logistics route;

[0091] Select the best route in the compliance areas and ensure that the selected logistics route only passes through areas that meet the compliance standards;

[0092] Dynamically adjust selected routes based on real-time data to ensure transportation paths always meet compliance standards.

[0093] The method to obtain the compliance code of the product is:

[0094] Extract basic product information from the supply chain management system and automatically import it, including product name, model, specification, production location, raw materials, and production process.

[0095] Based on the basic information of the product, query the pre-established compliance standards database, which includes the compliance requirements of products in different regions, countries, and industries;

[0096] Compliance standards include quality certification, environmental protection requirements, safety standards, and import and export regulations;

[0097] Classify products into relevant compliance standard categories based on product type and purpose;

[0098] Generate a unique compliance code based on preset rules and product compliance requirements. The code includes: product industry code, applicable regulations, applicable country code, and version number;

[0099] After obtaining the compliance code, verification is performed to ensure that the product compliance code is consistent with the actual compliance requirements.

[0100] By extracting basic product information from the supply chain management system and matching it with the compliance standards database, compliance codes are automatically generated to ensure that the compliance requirements of each product can be accurately identified and implemented. The generated compliance codes include industry codes, applicable regulations, country codes, and version numbers, ensuring the comprehensiveness and accuracy of compliance information and reducing the risk of human errors and missed reviews; the solution automatically classifies products into the correct compliance standard category based on product type, use, and related compliance requirements, and generates compliance codes that meet local market requirements based on regulatory requirements in different regions and countries, further ensuring that products comply with international or regional specific regulatory requirements.

[0101] Different countries and regions have different compliance requirements, especially in terms of quality, environment, safety, and import and export. This solution makes the generation process of compliance codes automatic and systematic through preset rules and compliance standard databases, which can quickly respond to various regulatory changes in cross-border trade and reduce the time for manual inspection, research and adjustment; this method ensures that each product has a unique compliance code, simplifies the compliance certification and review process, and enables all parties in the cross-border supply chain (such as suppliers, logistics companies, customs, etc.) to conduct product compliance verification and communication more efficiently, shorten customs clearance time, and reduce the complexity of compliance management.

[0102] After the compliance code is generated, the solution provides a compliance code verification mechanism to ensure that the generated compliance code is consistent with the actual regulatory requirements. This verification step can eliminate compliance errors and omissions before the product is launched, reducing the legal liability and potential market penalty risks caused by compliance issues; as the laws and regulations of various countries are updated and changed, the generation and verification of automated compliance codes can quickly adapt to new compliance standards, reduce the risk of non-compliance caused by legal changes, and ensure that products always meet the latest regulatory requirements.

[0103] The method for analyzing the areas that meet the compliance standards based on the compliance codes is as follows:

[0104] Decode compliance codes and identify region-specific information.

[0105] Use the compliance standards database to query the regional regulations corresponding to the code;

[0106] Combine certification marks and regulatory requirements to determine applicable markets and regions.

[0107] By decoding the compliance code and extracting the regional information, the applicable markets and regions of the product can be quickly identified. This ensures that the product can quickly adapt to the compliance requirements of different countries or regions, such as quality certification, environmental protection standards, safety regulations, etc., thereby effectively avoiding compliance errors caused by differences in regional regulations; the solution can automatically determine whether the product meets the regulatory requirements of the target market by querying the compliance standard database and combining the regional information in the code. This reduces the cost of understanding and adapting to different regulations when entering new markets, and improves compliance and product market competitiveness.

[0108] Automatically analyzing compliance codes and matching relevant regulatory information can significantly reduce the workload of manual query and review. By automatically querying the compliance standard database and matching the corresponding regional regulations, it not only improves the processing speed, but also reduces human errors and ensures the accuracy and consistency of information; with the continuous updating of regional regulations, the automated system can obtain the latest regulatory requirements in a timely manner, and automatically update through the compliance coding analysis system, helping enterprises to adapt to regulatory changes more quickly and reduce the tedious work of manual follow-up and adjustment.

[0109] By combining certification marks and regional regulatory requirements, compliance risks caused by regulatory mismatches can be effectively avoided. For example, some markets may require specific certification marks or test reports, and automated analysis can ensure that all regulatory requirements have been met before entering the market, thereby avoiding potential legal disputes or market penalties; for markets in different regions, especially in cross-border trade, compliance requirements may be complex and changeable. Through this solution, companies can quickly determine the compliance of products in specific regions, simplify the process of entering new markets, shorten approval and certification time, and reduce barriers to market entry.

[0110] The method of calculating the optimal logistics route using a dynamic optimization algorithm is:

[0111] Initialize the pheromone value for each path, and set the initial pheromone value of all paths to be the same;

[0112] Set according to the initial quality of the path;

[0113] Each ant chooses the path to take next based on probability. The selection probability formula is as follows:

[0114]

[0115] Where Pij is the probability of an ant choosing from node i to node j, τij is the pheromone concentration on the path (i, j), ηij is the heuristic function, α and β are the influencing factors of the pheromone and the heuristic function respectively, and J is the set of selectable paths. Ants complete the path planning of a delivery by selecting a path until all ants complete a round of path search;

[0116] The pheromones on all paths will evaporate at a certain ratio, which can be expressed as:

[0117] τ ij =(1-ρ)·τ ij

[0118] Among them, ρ is the pheromone evaporation rate, τij is the pheromone concentration on path (i, j);

[0119] After each round of iteration, the pheromones on the path are updated based on the quality of the ants’ path;

[0120] τ ij =τ ij +Δτ ij

[0121] Among them, Δτij is the amount of pheromone added on each path, which is inversely proportional to the quality of the path;

[0122]

[0123] Among them, Q is a constant and L is the total cost;

[0124] After each round of ant search, the best path in the current search is recorded and the global optimal solution is updated;

[0125] When the preset maximum number of iterations is reached or the preset convergence condition is met, the algorithm stops.

[0126] This scheme uses ants to select paths and update pheromones, so that the algorithm can adjust the path planning according to the actual situation after each iteration to adapt to the changes in demand in the logistics system. This adaptive mechanism is particularly suitable for solving logistics problems with strong uncertainty; the ant colony algorithm can flexibly handle multiple optimization goals, such as the shortest path, the lowest transportation cost, the lowest carbon emissions, etc., and can consider multiple goals at the same time in the logistics process to improve the overall transportation efficiency.

[0127] Through the pheromone update and evaporation mechanism, the ant colony can avoid falling into the local optimal solution during the search process. The evaporation of pheromones makes outdated or low-quality paths gradually ignored, thereby enhancing the global nature of the search and helping the algorithm find the global optimal solution or a path close to the optimal solution; ants perform path searches independently, and they explore different paths in parallel. This distributed search method significantly improves the efficiency of the algorithm and avoids the blindness of a single search process.

[0128] After each round of iteration, the algorithm will update the pheromone according to the quality of the ants' paths. The better paths will be "reinforced" more, prompting more ants to choose these paths. This mechanism makes the search more accurate and efficient by strengthening effective paths and eliminating suboptimal paths. The pheromone adjustment after each path search depends on the quality of the path (such as total transportation cost, distance, etc.). This mechanism ensures that the path quality is continuously optimized and can make real-time adjustments based on the results of each round, ultimately finding the optimal logistics route that meets current needs.

[0129] The ant colony algorithm can effectively handle large-scale logistics problems with a large number of nodes and paths, such as complex logistics networks such as inter-city distribution and cross-border transportation. Ants perform path search on a global scale through distributed computing, adapting to the growth of nodes and paths in large-scale logistics environments; the algorithm uses repeated iterations and pheromone evaporation mechanisms to continuously optimize logistics paths even when demand and constraints are uncertain and the environment changes rapidly, thereby maintaining efficient operation in complex and dynamic logistics environments.

[0130] The basic principle of the ant colony algorithm is simple, easy to understand and implement. By introducing heuristic functions, pheromone evaporation and other mechanisms, it can be flexibly combined with actual logistics needs, and the path selection rules can be adjusted to meet the needs of different scenarios (such as time windows, cargo restrictions, etc.); by adjusting the key parameters in the algorithm (such as pheromone influence factors, evaporation rates, heuristic factors, etc.), the behavior of the algorithm can be adjusted according to different logistics scenarios, so as to find the appropriate logistics path in different situations.

[0131] The method of selecting the best route in the compliance area and ensuring that the selected logistics route only passes through areas that meet the compliance standards is:

[0132] During the path selection process, ensure that the selected logistics routes only pass through areas that meet the compliance standards, and eliminate any paths that include areas that do not meet the compliance standards.

[0133] This embodiment also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the supply chain management method for cross-border trade as described above when executing the computer program.

[0134] This embodiment also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the supply chain management method for cross-border trade as described above is implemented.

[0135] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM). Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0136] The above embodiments of the present invention are not intended to limit the protection scope of the present invention, and the implementation modes of the present invention are not limited thereto. All other modifications, replacements or changes made to the above structures of the present invention based on the above contents of the present invention, in accordance with common technical knowledge and customary means in the art, without departing from the above basic technical ideas of the present invention, should fall within the protection scope of the present invention.

Claims

1. A supply chain management system for cross-border trade, characterized in that: Included are: A blockchain network to store and manage all data related to the supply chain and ensure data immutability and transparency; A compliance code generation module, used to generate a unique product code according to the product type and product information of each product, and generate a compliance number for each region based on the compliance conditions of each region that the current product complies with. If the product meets the compliance requirements of a region, a compliance number is generated for the region, otherwise no compliance number is generated. The compliance number is composed of multiple regional compliance numbers; The data collection module collects logistics status and environmental data in real time through sensors and IoT devices, and uploads the data to the blockchain network; Route optimization module, based on compliance coding and real-time data analysis, uses dynamic optimization algorithms to calculate the optimal logistics route, ensuring that the product's logistics route only passes through areas that meet compliance requirements; The user interface module provides a user interface for participants to query and operate information.

2. The supply chain management system for cross-border trade according to claim 1, characterized in that: Participants in the blockchain network include manufacturers, suppliers, logistics companies and customs, and each participant can access and update product-related data in real time.

3. The supply chain management system for cross-border trade according to claim 1, characterized in that: The system further includes an early warning module for issuing a warning and prompting the route to be adjusted when the system detects non-compliant areas in the logistics route.

4. A supply chain management method for cross-border trade, characterized in that: The following steps are involved: Obtain compliance codes for products; Analyze the areas that meet the compliance standards based on the compliance codes; Collect real-time logistics data, including traffic conditions, weather conditions, and checkpoint traffic conditions; Use dynamic optimization algorithms to calculate the optimal logistics route; Select the best route in the compliance areas and ensure that the selected logistics route only passes through areas that meet the compliance standards; Dynamically adjust selected routes based on real-time data to ensure transportation paths always meet compliance standards.

5. The supply chain management method for cross-border trade according to claim 4, characterized in that: The method to obtain the compliance code of the product is: Extract basic product information from the supply chain management system and automatically import it, including product name, model, specification, production location, raw materials, and production process. Based on the basic information of the product, query the pre-established compliance standards database, which includes the compliance requirements of products in different regions, countries, and industries; Compliance standards include quality certification, environmental protection requirements, safety standards, and import and export regulations; Classify products into relevant compliance standard categories based on product type and purpose; Generate a unique compliance code based on preset rules and product compliance requirements. The code includes: product industry code, applicable regulations, applicable country code, and version number; After obtaining the compliance code, verification is performed to ensure that the product compliance code is consistent with the actual compliance requirements.

6. The supply chain management method for cross-border trade according to claim 4, characterized in that: The method for analyzing the areas that meet the compliance standards based on the compliance codes is as follows: Decode compliance codes and identify region-specific information. Use the compliance standards database to query the regional regulations corresponding to the code; Combine certification marks and regulatory requirements to determine applicable markets and regions.

7. The supply chain management method for cross-border trade according to claim 4, characterized in that: The method of calculating the optimal logistics route using a dynamic optimization algorithm is: Initialize the pheromone value for each path, and set the initial pheromone value of all paths to be the same; Set according to the initial quality of the path; Each ant chooses the path to take next based on probability. The selection probability formula is as follows: Where Pij is the probability of an ant choosing from node i to node j, τij is the pheromone concentration on the path (i, j), ηij is the heuristic function, α and β are the influencing factors of the pheromone and the heuristic function respectively, and J is the set of selectable paths. Ants complete the path planning of a delivery by selecting a path until all ants complete a round of path search; The pheromones on all paths will evaporate at a certain ratio, which can be expressed as: t ij =(1-ρ)·τ ij Among them, ρ is the pheromone evaporation rate, τij is the pheromone concentration on path (i, j); After each round of iteration, the pheromones on the path are updated based on the quality of the ants’ path; t ij =t ij +Δt ij Among them, Δτij is the amount of pheromone added on each path, which is inversely proportional to the quality of the path; Among them, Q is a constant and L is the total cost; After each round of ant search, the best path in the current search is recorded and the global optimal solution is updated; When the preset maximum number of iterations is reached or the preset convergence condition is met, the algorithm stops.

8. The supply chain management method for cross-border trade according to claim 4, characterized in that: The method of selecting the best route in the compliance area and ensuring that the selected logistics route only passes through areas that meet the compliance standards is: During the path selection process, ensure that the selected logistics routes only pass through areas that meet the compliance standards, and eliminate any paths that include areas that do not meet the compliance standards.

9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, the supply chain management method for cross-border trade as described in any one of claims 4 to 8 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the supply chain management method for cross-border trade as described in any one of claims 4 to 8 is implemented.

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