Intelligent logistics supply chain management system

Abstract

The invention discloses an intelligent logistics supply chain management system, and the system comprises a block chain information sharing platform which is responsible for building an information sharing platform based on a block chain, inviting all participants on the supply chain to join, and storing and transmitting the data of each link of the supply chain through the distributed account book technology of the block chain; the product information tracing system is responsible for distributing a unique block chain ID for each fresh food and recording the circulation process of the fresh food in a supply chain; and the collaborative management platform is responsible for integrating and uniformly managing data of purchasing, warehousing, transportation and sales, predicting future sales trend and inventory demand change by using a random forest according to historical sales data and market trend information, and optimizing an inventory level, a reorder strategy, a sales strategy and a promotion activity plan in combination with a genetic algorithm, so as to achieve the purpose of sales promotion. The inventory cost is minimized, the sales demand is met, and the block chain information sharing platform and the collaborative management platform carry out data synchronization.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics supply chain management, and in particular to an intelligent logistics supply chain management system. Background Art

[0002] Logistics supply chain management refers to a management model that integrates and coordinates the various links in the logistics supply chain to optimize logistics services and improve customer value. It covers the entire logistics process from suppliers to end users, including raw material procurement, processing, logistics transportation, distribution, and customer service, and uniformly manages and coordinates the information flow, logistics, and capital flow in these links. Logistics supply chain management can improve the efficiency and accuracy of the entire supply chain, reduce logistics costs and losses, and at the same time strengthen contact and communication with suppliers and customers, and improve customer satisfaction and loyalty.

[0003] In the prior art, the supply chain of fresh food usually involves multiple links, including procurement, warehousing, transportation and sales. The synergy between these links is crucial to ensure the freshness and safety of food. However, in actual operation, due to the differences in the interests and operation methods of each link, especially between warehousing and sales, the synergy is insufficient. Therefore, an intelligent logistics supply chain management system is proposed. Summary of the invention

[0004] The purpose of the present invention is to solve the problem in the prior art that the supply chain of fresh food usually involves multiple links, including procurement, warehousing, transportation and sales. The synergy between these links is crucial to ensure the freshness and safety of food. However, in actual operation, due to the differences in the interests and operation methods of each link, especially between procurement, warehousing and sales, there is a shortcoming of insufficient synergy, and an intelligent logistics supply chain management system is proposed.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] An intelligent logistics supply chain management system, comprising:

[0007] Blockchain information sharing platform: responsible for establishing a blockchain-based information sharing platform, inviting all participants in the supply chain, such as suppliers, manufacturers, distributors, and retailers, to join, using the distributed ledger technology of blockchain to store and transmit data from all links of the supply chain, including product information, inventory status, order status, transportation progress, etc., setting different access rights for different participants to ensure the privacy and security of information, and introducing smart contracts to automatically execute transactions and processes in the supply chain, such as payment, shipment, receipt, etc. The blockchain information sharing platform receives data from the product information traceability system;

[0008] Product information traceability system: responsible for assigning a unique blockchain ID to each fresh food and recording its circulation process in the supply chain. The product information traceability system shares the complete supply chain information of the product with other stakeholders in the supply chain through a collaborative management platform;

[0009] Collaborative management platform: responsible for integrating and uniformly managing the data of procurement, warehousing, transportation and sales, providing a comprehensive supply chain view, using random forests to predict future sales trends and inventory demand changes based on historical sales data and market trend information, and combining genetic algorithms to optimize inventory levels, reordering strategies, sales strategies and promotional activity plans to minimize inventory costs and meet sales needs. The blockchain information sharing platform synchronizes data with the collaborative management platform;

[0010] Monitoring and early warning system: responsible for providing a monitoring interface, displaying the real-time status and key indicators of the supply chain, and setting up an early warning mechanism. When an abnormality or potential risk occurs in a certain link in the supply chain, it will automatically issue an early warning and give corresponding processing suggestions. At the same time, it will predict future trends and changes through data analysis to provide support for decision-making.

[0011] The above technical solution further includes:

[0012] Preferably, the blockchain information sharing platform includes a blockchain network module, a data storage and transmission module, a rights management module and a smart contract module. The blockchain network module is responsible for creating and maintaining the blockchain network, including node management, consensus mechanism, data verification, etc. The blockchain network module interacts with the data storage and transmission module to write the supply chain data into the blockchain. The blockchain network module interacts with the rights management module to ensure the legitimacy of the node identity and the privacy of the data. The data storage and transmission module uses the distributed ledger technology of the blockchain to safely and efficiently store and transmit data in various links of the supply chain. The data storage and transmission module interacts with the blockchain network module, receives and verifies the data and writes it into the blockchain. The data storage and transmission module interacts with the systems of each supply chain participant (such as suppliers, manufacturers, distributors, retailers) to obtain and transmit the supply chain data. The data storage and transmission module interacts with the smart contract module. The rights management module interacts with the systems of each supply chain participant and allows or denies access to specific data based on the rights settings. The smart contract module deploys smart contracts on the blockchain to achieve automated transactions and collaboration between all parties in the supply chain. The smart contract module interacts with the data storage and transmission module to obtain relevant data and perform corresponding data operations based on the triggering conditions of the smart contract. The smart contract module interacts with the systems of each supply chain participant, sends transaction requests and receives transaction results. The smart contract module interacts with the blockchain network module to ensure that the execution results of the smart contract are correctly recorded and verified.

[0013] Preferably, the blockchain network module creates and maintains a blockchain network, comprising the following steps:

[0014] Node management: Identify the nodes of all parties involved in the blockchain network, including suppliers, manufacturers, distributors, retailers, and regulators. Then, assign a unique identifier (such as a public and private key pair) to each node to ensure the identity security and traceability of the node. Node management ensures that only legitimate participants can join the network, thereby maintaining the integrity and security of the network.

[0015] Consensus mechanism: In the supply chain of fresh food, the Practical Byzantine Fault Tolerant (PBFT) consensus mechanism is selected. If a node proposes a new block (including transactions or data), the node will send a request to other nodes in the network for verification. If more than half of the nodes verify the validity of the block and reach a consensus, the block will be added to the blockchain.

[0016] Data Verification: When new blocks are added to the blockchain, nodes in the network verify them to ensure the accuracy and integrity of the data.

[0017] Preferably, the data storage and transmission module utilizes the distributed ledger technology of blockchain to store and transmit data of various links in the supply chain, including the following steps:

[0018] Data collection and preprocessing: Collect data from the fresh food supply chain and preprocess it;

[0019] Data encryption and signature: Before uploading data to the blockchain, it is encrypted and a digital signature is generated. The logical formula for encryption is Encrypted_Data = Encrypt (Raw_Data), and the logical formula for signature is Signed_Data = Sign (Encrypted_Data), where Encrypt represents the encryption function and Sign represents the signature function;

[0020] Data upload and storage: The encrypted and signed data will be uploaded to the distributed ledger of the blockchain. The distributed nature of the blockchain ensures the high availability and fault tolerance of the data. Even if some nodes fail, the data can still be recovered from other nodes.

[0021] Preferably, the product information tracing system allocates a blockchain ID and records the specific steps of its circulation process in the supply chain:

[0022] Product registration and ID allocation: Before fresh food enters the supply chain, it is registered on the blockchain platform. During the registration process, the product information traceability system allocates a unique blockchain ID to each product. The blockchain ID corresponds to the physical entity of the product one by one to ensure the uniqueness and traceability of the product. The formula for allocating a unique blockchain ID is Product_ID = Hash (Product_Info), where Product_ID is the product blockchain ID, Product_Info is the product registration information (such as product name, production date, production batch, etc.), and Hash is a hash function used to generate a unique identifier;

[0023] Supply chain information entry: In the supply chain of fresh food, each link (such as raw material procurement, production and processing, quality inspection, packaging, transportation, sales, etc.) will enter relevant information into the blockchain platform. The relevant information includes but is not limited to the source of raw materials, production date, production batch, quality inspection report, transportation method, transportation time, transportation temperature, etc. The input logic formula is Supply_Chain_Data = {Step1_Data, Step2_Data, ..., StepN_Data}, where Supply_Chain_Data is the supply chain information set, and Step1_Data, Step2_Data, ..., StepN_Data are the information of each link of the supply chain respectively;

[0024] Information verification and storage: After the supply chain information is entered, the nodes in the blockchain network will verify the information to ensure its authenticity and accuracy. After the verification, the information will be stored on the blockchain to form an unalterable historical record. The verification logic formula is Verified_Data = Validate (Supply_Chain_Data), where Verified_Data is the verified supply chain information and Validate is a verification function used to check the authenticity and accuracy of the information.

[0025] Information query and tracking: Consumers or related parties can query the complete supply chain information of the product on the blockchain platform by scanning the QR code on the product or entering the blockchain ID. The query logic formula is Query_Result = Query(Product_ID), where Query_Result is the query result and Query is the query function, which is used to obtain supply chain information based on the product blockchain ID.

[0026] Preferably, the collaborative management platform includes a procurement management module, a warehousing management module, a transportation management module, a sales management module and a data analysis and decision support module. The procurement management module is responsible for the formulation and execution of procurement plans, the warehousing management module is responsible for real-time monitoring and management of inventory, the transportation management module is responsible for the formulation and execution of transportation plans, real-time tracking of transportation progress and cargo status, and ensuring timely and safe transportation. The sales management module is responsible for real-time monitoring and analysis of sales data, providing sales forecasts and market demand analysis, and the data analysis and decision support module is responsible for analyzing and mining supply chain data, using random forests to predict future sales trends and inventory demand changes based on historical sales data and market trend information, and combining genetic algorithms to optimize inventory levels, reordering strategies, sales strategies, and promotional activity plans to minimize inventory costs and meet sales needs.

[0027] Preferably, the specific steps of using random forest to predict future sales trends and inventory demand changes are:

[0028] Data preparation: Collect historical sales data, including sales quantity, sales time, sales price, etc., and collect market trend information, such as seasonal changes, holiday impacts, competitor dynamics, etc.;

[0029] Data preprocessing: clean historical sales data, remove outliers and missing values, and quantify market trend information, such as converting seasonal changes into seasonal indices;

[0030] Constructing a random forest model: Using decision trees as base learners, construct multiple decision trees to form a random forest. Multiple sample sets are extracted from the training set through bootstrap sampling to train each decision tree. When each node is split, some attributes are randomly selected for splitting to improve the generalization ability of the model.

[0031] Model training and prediction: Use historical sales data and market trend information as input to train the random forest model, and use the trained model to predict future sales trends and inventory demand changes.

[0032] Preferably, the optimization of inventory levels, reordering strategies, sales strategies and promotional activity plans in combination with genetic algorithms comprises the following steps:

[0033] Define optimization goals: minimize inventory costs, including inventory holding costs, out-of-stock costs, etc., meet sales demand, and ensure that inventory levels can support sales activities;

[0034] Encoding and initialization: Encoding parameters, including inventory levels, reorder points, sales strategies, and promotion activity plans, and initializing a population containing multiple different parameter combinations;

[0035] Fitness function design: According to the optimization goal, a fitness function is designed to evaluate the pros and cons of each parameter combination scheme;

[0036] Assume several key variables and parameters:

[0037] Inventory cost: This usually includes inventory holding cost and stockout cost. Inventory holding cost refers to the cost required to hold inventory, such as storage fees, insurance premiums, etc.; stockout cost refers to indirect costs such as sales loss and reduced customer satisfaction caused by insufficient inventory.

[0038] Sales Fulfillment Rate (SFR): This refers to the ratio between actual sales volume and customer demand, which is used to measure the ability of inventory strategy to meet sales demand.

[0039] Next, we design a fitness function F, which takes inventory cost and sales satisfaction rate as input and outputs a comprehensive evaluation value. The higher this value is, the better the parameter combination scheme is.

[0040] The formula of the fitness function F is as follows: F = w1*(SFR / SFR_max)+w2*(1-IC / IC_max), where: w1 and w2 are weight coefficients used to adjust the relative importance of sales satisfaction rate and inventory cost in the fitness function. These weights can be set according to the specific needs and preferences of the enterprise; SFR_max is the maximum possible value of the sales satisfaction rate, usually set to 1 (indicating full satisfaction of sales demand); IC_max is the maximum possible value of inventory cost, which needs to be estimated based on the company's historical data or industry standards.

[0041] Genetic operations: Selection: According to the fitness function value, select individuals with higher fitness as parents to generate the next generation; Crossover: Perform crossover operations on parent individuals to generate new offspring individuals; Mutation: Perform mutation operations on offspring individuals to increase the diversity of the population;

[0042] Iterative optimization: Repeat the selection, crossover and mutation operations to generate a new population. According to the fitness function value, continuously select better parameter combination schemes until the predetermined number of iterations is reached or the fitness function value is no longer significantly improved. Continuously iterate and evolve the individuals in the population (i.e., parameter combination schemes), and use the fitness function to evaluate the quality of each individual. In each iteration, a part of the individuals will be selected as the parent generation according to the fitness value to perform crossover and mutation operations to generate new offspring individuals.

[0043] The present invention has the following beneficial effects:

[0044] In the present invention, the collaborative management platform uses random forests to predict future sales trends and inventory demand changes based on historical sales data and market trend information, and combines genetic algorithms to optimize inventory levels, reorder strategies, sales strategies, and promotional activity plans to minimize inventory costs and meet sales demand, thereby ensuring the synergy between warehousing and sales. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a system architecture diagram of an intelligent logistics supply chain management system proposed by the present invention. DETAILED DESCRIPTION

[0046] 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.

[0047] like Figure 1 As shown, an intelligent logistics supply chain management system includes:

[0048] Blockchain information sharing platform: responsible for establishing a blockchain-based information sharing platform, inviting all participants in the supply chain, such as suppliers, manufacturers, distributors, and retailers, to join, using the distributed ledger technology of blockchain to store and transmit data from all links of the supply chain, including product information, inventory status, order status, transportation progress, etc., setting different access rights for different participants to ensure the privacy and security of information, and introducing smart contracts to automatically execute transactions and processes in the supply chain, such as payment, shipment, receipt, etc. The blockchain information sharing platform receives data from the product information traceability system;

[0049] Product information traceability system: responsible for assigning a unique blockchain ID to each fresh food and recording its circulation process in the supply chain. The product information traceability system shares the complete supply chain information of the product with other stakeholders in the supply chain through the collaborative management platform;

[0050] Collaborative management platform: responsible for integrating and uniformly managing procurement, warehousing, transportation and sales data, providing a comprehensive supply chain view, using random forests to predict future sales trends and inventory demand changes based on historical sales data and market trend information, and combining genetic algorithms to optimize inventory levels, reordering strategies, sales strategies and promotional activity plans to minimize inventory costs and meet sales needs. The blockchain information sharing platform synchronizes data with the collaborative management platform;

[0051] Monitoring and early warning system: responsible for providing a monitoring interface, displaying the real-time status and key indicators of the supply chain, and setting up an early warning mechanism. When an abnormality or potential risk occurs in a certain link in the supply chain, it will automatically issue an early warning and give corresponding processing suggestions. At the same time, it will predict future trends and changes through data analysis to provide support for decision-making.

[0052] In one embodiment, the blockchain information sharing platform includes a blockchain network module, a data storage and transmission module, a rights management module and a smart contract module. The blockchain network module is responsible for creating and maintaining the blockchain network, including node management, consensus mechanism, data verification, etc. The blockchain network module interacts with the data storage and transmission module to write the supply chain data into the blockchain. The blockchain network module interacts with the rights management module to ensure the legitimacy of the node identity and the privacy of the data. The data storage and transmission module uses the distributed ledger technology of the blockchain to safely and efficiently store and transmit data in various links of the supply chain. The data storage and transmission module interacts with the blockchain network module and writes the data into the blockchain after receiving and verifying the data. The data storage and transmission module interacts with the systems of each supply chain participant (such as suppliers, manufacturers, distributors, and retailers) to obtain and transmit the supply chain data. The data storage and transmission module interacts with the smart contract The modules interact with each other and perform corresponding data operations according to the triggering conditions of the smart contract. The permission management module sets different access rights for different participants to ensure the privacy and security of information. The permission management module interacts with the blockchain network module to verify the legitimacy of the node identity and the privacy of the data. The permission management module interacts with the systems of each supply chain participant and allows or denies access to specific data based on the permission settings. The smart contract module deploys smart contracts on the blockchain to realize automated transactions and collaboration between all parties in the supply chain. The smart contract module interacts with the data storage and transmission module to obtain relevant data and perform corresponding data operations according to the triggering conditions of the smart contract. The smart contract module interacts with the systems of each supply chain participant, sends transaction requests and receives transaction results. The smart contract module interacts with the blockchain network module to ensure that the execution results of the smart contract are correctly recorded and verified.

[0053] In one embodiment, the blockchain network module creates and maintains a blockchain network, including the following steps:

[0054] Node management: Identify the nodes of all parties participating in the blockchain network, including suppliers, manufacturers, distributors, retailers, and regulators. Then, assign a unique identifier (such as a public and private key pair) to each node to ensure the identity security and traceability of the node. Node management ensures that only legitimate participants can join the network, thereby maintaining the integrity and security of the network.

[0055] Consensus mechanism: In the supply chain of fresh food, the Practical Byzantine Fault Tolerant (PBFT) consensus mechanism is selected. If a node proposes a new block (including transactions or data), the node will send a request to other nodes in the network for verification. If more than half of the nodes verify the validity of the block and reach a consensus, the block will be added to the blockchain.

[0056] Data Verification: When new blocks are added to the blockchain, nodes in the network verify them to ensure the accuracy and integrity of the data.

[0057] Suppose a supplier sends a batch of fresh food to a producer. On the blockchain, this transaction is recorded as a new block. Before adding the block, nodes in the network verify the authenticity of the transaction (such as the identity of the supplier, the quantity and quality of the product, the date and location of the shipment, etc.). If the verification is successful, the block is added to the blockchain and becomes an immutable historical record.

[0058] In one embodiment, the data storage and transmission module uses the distributed ledger technology of blockchain to store and transmit data from various links of the supply chain, including the following steps:

[0059] Data collection and preprocessing: Collect data from the fresh food supply chain and preprocess it;

[0060] Data encryption and signature: Before uploading data to the blockchain, it is encrypted and a digital signature is generated. The logical formula for encryption is Encrypted_Data = Encrypt (Raw_Data), and the logical formula for signature is Signed_Data = Sign (Encrypted_Data), where Encrypt represents the encryption function and Sign represents the signature function;

[0061] Data upload and storage: The encrypted and signed data will be uploaded to the distributed ledger of the blockchain. The distributed nature of the blockchain ensures the high availability and fault tolerance of the data. Even if some nodes fail, the data can still be recovered from other nodes.

[0062] In one embodiment, the product information traceability system allocates a blockchain ID and records the specific steps of its circulation process in the supply chain:

[0063] Product registration and ID allocation: Before fresh food enters the supply chain, it is registered on the blockchain platform. During the registration process, the product information traceability system assigns a unique blockchain ID to each product. The blockchain ID corresponds to the physical entity of the product one by one to ensure the uniqueness and traceability of the product. The formula for assigning a unique blockchain ID is Product_ID = Hash (Product_Info), where Product_ID is the product blockchain ID, Product_Info is the product registration information (such as product name, production date, production batch, etc.), and Hash is a hash function used to generate a unique identifier;

[0064] Supply chain information entry: In the supply chain of fresh food, each link (such as raw material procurement, production and processing, quality inspection, packaging, transportation, sales, etc.) will enter relevant information into the blockchain platform. The relevant information includes but is not limited to the source of raw materials, production date, production batch, quality inspection report, transportation method, transportation time, transportation temperature, etc. The input logic formula is Supply_Chain_Data = {Step1_Data, Step2_Data, ..., StepN_Data}, where Supply_Chain_Data is the supply chain information set, and Step1_Data, Step2_Data, ..., StepN_Data are the information of each link of the supply chain respectively;

[0065] Information verification and storage: After the supply chain information is entered, the nodes in the blockchain network will verify the information to ensure its authenticity and accuracy. After verification, the information will be stored on the blockchain to form an unalterable historical record. The verification logic formula is Verified_Data = Validate (Supply_Chain_Data), where Verified_Data is the verified supply chain information and Validate is a verification function used to check the authenticity and accuracy of the information.

[0066] Information query and tracking: Consumers or related parties can query the complete supply chain information of the product on the blockchain platform by scanning the QR code on the product or entering the blockchain ID. The query logic formula is Query_Result = Query(Product_ID), where Query_Result is the query result and Query is the query function, which is used to obtain supply chain information based on the product blockchain ID.

[0067] Product Registration and ID Allocation:

[0068] Supplier A registers a batch of fresh food on the blockchain platform and assigns a unique blockchain ID to each product.

[0069] For example, the blockchain ID of a product is "ABCD1234".

[0070] Supply chain information entry:

[0071] During the raw material procurement process, Supplier A enters the source information of the raw materials into the blockchain.

[0072] During the production and processing stage, manufacturer B enters information such as production date, production batch, quality inspection report, etc. into the blockchain.

[0073] During the packaging process, manufacturer B also enters information such as packaging materials and packaging date into the blockchain.

[0074] During the transportation process, distributor C enters information such as transportation method, transportation time, and transportation temperature into the blockchain.

[0075] During the sales process, retailer D enters information such as sales location and sales date into the blockchain.

[0076] Information verification and storage:

[0077] Nodes in the blockchain network verify supply chain information to ensure its authenticity and accuracy.

[0078] After verification, the information is stored on the blockchain, forming an unalterable historical record.

[0079] Information query and tracking:

[0080] After purchasing a product, consumers can query the complete supply chain information of the product on the blockchain platform by scanning the QR code on the product or entering the blockchain ID "ABCD1234".

[0081] This includes information such as the source of raw materials, production date, production batch, quality inspection report, transportation method, transportation time, transportation temperature, sales location, etc.

[0082] Through this information, consumers can understand the entire journey of the product and ensure its quality and safety.

[0083] In one embodiment, the collaborative management platform includes a procurement management module, a warehousing management module, a transportation management module, a sales management module, and a data analysis and decision support module. The procurement management module is responsible for the formulation and execution of procurement plans, the warehousing management module is responsible for real-time monitoring and management of inventory, the transportation management module is responsible for the formulation and execution of transportation plans, real-time tracking of transportation progress and cargo status, and ensuring timeliness and safety of transportation. The sales management module is responsible for real-time monitoring and analysis of sales data, providing sales forecasts and market demand analysis, and the data analysis and decision support module is responsible for analyzing and mining supply chain data, using random forests to predict future sales trends and inventory demand changes based on historical sales data and market trend information, and combining genetic algorithms to optimize inventory levels, reordering strategies, sales strategies, and promotional activity plans to minimize inventory costs and meet sales needs.

[0084] In one embodiment, the specific steps of using random forest to predict future sales trends and inventory demand changes are:

[0085] Data preparation: Collect historical sales data, including sales quantity, sales time, sales price, etc., and collect market trend information, such as seasonal changes, holiday impacts, competitor dynamics, etc.;

[0086] Data preprocessing: clean historical sales data, remove outliers and missing values, and quantify market trend information, such as converting seasonal changes into seasonal indices;

[0087] Constructing a random forest model: Using decision trees as base learners, construct multiple decision trees to form a random forest. Multiple sample sets are extracted from the training set through bootstrap sampling to train each decision tree. When each node is split, some attributes are randomly selected for splitting to improve the generalization ability of the model.

[0088] Model training and prediction: Use historical sales data and market trend information as input to train the random forest model, and use the trained model to predict future sales trends and inventory demand changes.

[0089] In one embodiment, optimizing inventory levels, reordering strategies, sales strategies, and promotional activity plans in combination with genetic algorithms includes the following steps:

[0090] Define optimization goals: minimize inventory costs, including inventory holding costs, out-of-stock costs, etc., meet sales demand, and ensure that inventory levels can support sales activities;

[0091] Encoding and initialization: Encode parameters, including inventory levels, reorder points, sales strategies, and promotional activity plans, and initialize a population containing multiple different parameter combinations;

[0092] Fitness function design: According to the optimization goal, a fitness function is designed to evaluate the pros and cons of each parameter combination scheme;

[0093] Assume several key variables and parameters:

[0094] Inventory cost: This usually includes inventory holding cost and stockout cost. Inventory holding cost refers to the cost required to hold inventory, such as storage fees, insurance premiums, etc.; stockout cost refers to indirect costs such as sales loss and reduced customer satisfaction caused by insufficient inventory.

[0095] Sales Fulfillment Rate (SFR): This refers to the ratio between actual sales volume and customer demand, which is used to measure the ability of inventory strategy to meet sales demand.

[0096] Next, we design a fitness function F, which takes inventory cost and sales satisfaction rate as input and outputs a comprehensive evaluation value. The higher this value is, the better the parameter combination scheme is.

[0097] The formula of the fitness function F is as follows: F = w1*(SFR / SFR_max)+w2*(1-IC / IC_max), where: w1 and w2 are weight coefficients used to adjust the relative importance of sales satisfaction rate and inventory cost in the fitness function. These weights can be set according to the specific needs and preferences of the enterprise; SFR_max is the maximum possible value of the sales satisfaction rate, usually set to 1 (indicating full satisfaction of sales demand); IC_max is the maximum possible value of inventory cost, which needs to be estimated based on the company's historical data or industry standards.

[0098] Genetic operations: Selection: According to the fitness function value, select individuals with higher fitness as parents to generate the next generation; Crossover: Perform crossover operations on parent individuals to generate new offspring individuals; Mutation: Perform mutation operations on offspring individuals to increase the diversity of the population;

[0099] Iterative optimization: Repeat the selection, crossover and mutation operations to generate a new population. According to the fitness function value, continuously select better parameter combination schemes until the predetermined number of iterations is reached or the fitness function value is no longer significantly improved. Continuously iterate and evolve the individuals in the population (i.e., parameter combination schemes), and use the fitness function to evaluate the quality of each individual. In each iteration, a part of the individuals will be selected as the parent generation according to the fitness value to perform crossover and mutation operations to generate new offspring individuals.

[0100] Assume that a fresh food supply chain company has multiple sales outlets, each of which needs to be replenished regularly. In order to minimize inventory costs and meet sales demand, the company can use random forests to predict future sales trends and inventory demand changes, and combine genetic algorithms to optimize inventory levels, reorder strategies, etc.

[0101] Collect historical sales data and market trend information, such as seasonal changes, holiday impacts, etc.

[0102] The data is preprocessed and features are extracted, and a random forest model is constructed for prediction.

[0103] Based on the forecast results, determine the sales trend and inventory demand changes in the future period.

[0104] Define optimization goals, such as minimizing inventory costs, meeting sales demand, etc.

[0105] Encode and initialize parameters such as inventory levels, reorder points, etc.

[0106] Design the fitness function, taking into account indicators such as inventory cost and sales satisfaction rate.

[0107] Perform genetic operations and continuously iterate and optimize parameter combination solutions.

[0108] Based on the optimization results, plans such as inventory levels and reordering strategies are formulated and applied in actual operations.

[0109] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent logistics supply chain management system, characterized in that: include: Blockchain information sharing platform: responsible for establishing a blockchain-based information sharing platform, inviting all participants in the supply chain to join, using blockchain's distributed ledger technology to store and transmit data from all links of the supply chain, setting different access rights for different participants, and introducing smart contracts to automatically execute transactions and processes in the supply chain. The blockchain information sharing platform receives data from the product information traceability system; Product information traceability system: responsible for assigning a unique blockchain ID to each fresh food and recording its circulation process in the supply chain. The product information traceability system shares the complete supply chain information of the product with other stakeholders in the supply chain through a collaborative management platform; Collaborative management platform: responsible for integrating and uniformly managing the data of procurement, warehousing, transportation and sales. Based on historical sales data and market trend information, it uses random forest to predict future sales trends and changes in inventory demand. At the same time, it combines genetic algorithms to optimize inventory levels, reorder strategies, sales strategies and promotional activity plans to minimize inventory costs and meet sales needs. The blockchain information sharing platform synchronizes data with the collaborative management platform. Monitoring and early warning system: responsible for providing a monitoring interface, displaying the real-time status and key indicators of the supply chain, and setting up an early warning mechanism. When an abnormality or potential risk occurs in a certain link in the supply chain, it will automatically issue an early warning and give corresponding processing suggestions. At the same time, it will predict future trends and changes through data analysis.

2. An intelligent logistics supply chain management system according to claim 1, characterized in that: The blockchain information sharing platform includes a blockchain network module, a data storage and transmission module, a rights management module and a smart contract module. The blockchain network module is responsible for creating and maintaining the blockchain network. The blockchain network module interacts with the data storage and transmission module to write the supply chain data into the blockchain. The blockchain network module interacts with the rights management module. The data storage and transmission module uses the distributed ledger technology of the blockchain to store and transmit data in various links of the supply chain. The data storage and transmission module interacts with the blockchain network module, receives and verifies the data and writes it into the blockchain. The data storage and transmission module interacts with the systems of each supply chain participant to obtain and transmit the supply chain data. The data storage and transmission module interacts with the smart contract module to trigger the smart contract according to the conditions. The rights management module performs corresponding data operations. The rights management module sets different access rights for different participants. The rights management module interacts with the blockchain network module to verify the legitimacy of the node identity and the privacy of the data. The rights management module interacts with the systems of each supply chain participant and allows or denies access to specific data based on the rights settings. The smart contract module deploys smart contracts on the blockchain to achieve automated transactions and collaboration between all parties in the supply chain. The smart contract module interacts with the data storage and transmission module to obtain relevant data and perform corresponding data operations based on the triggering conditions of the smart contract. The smart contract module interacts with the systems of each supply chain participant, sends transaction requests and receives transaction results. The smart contract module interacts with the blockchain network module.

3. An intelligent logistics supply chain management system according to claim 2, characterized in that: The blockchain network module creates and maintains a blockchain network, including the following steps: Node management: Identify the nodes of all parties participating in the blockchain network, including suppliers, manufacturers, distributors, retailers, and regulators, and then assign a unique identifier to each node; Consensus mechanism: In the supply chain of fresh food, the Practical Byzantine Fault Tolerant (PBFT) consensus mechanism is selected. If a node proposes a new block, it will send a request to other nodes in the network for verification. If more than half of the nodes verify the validity of the block and reach a consensus, the block will be added to the blockchain. Data Verification: When a new block is added to the blockchain, it is verified by nodes in the network.

4. An intelligent logistics supply chain management system according to claim 2, characterized in that: The data storage and transmission module uses the distributed ledger technology of blockchain to store and transmit data from various links of the supply chain, including the following steps: Data collection and preprocessing: Collect data from the fresh food supply chain and preprocess it; Data encryption and signature: Before uploading data to the blockchain, it is encrypted and a digital signature is generated. The logical formula for encryption is Encrypted_Data = Encrypt (Raw_Data), and the logical formula for signature is Signed_Data = Sign (Encrypted_Data), where Encrypt represents the encryption function and Sign represents the signature function; Data upload and storage: The encrypted and signed data will be uploaded to the distributed ledger of the blockchain.

5. The intelligent logistics supply chain management system according to claim 1 is characterized in that: The product information traceability system allocates a blockchain ID and records the specific steps of its circulation process in the supply chain: Product registration and ID allocation: Before fresh food enters the supply chain, it is registered on the blockchain platform. During the registration process, the product information traceability system allocates a unique blockchain ID to each product. The blockchain ID corresponds to the physical entity of the product one by one. The formula for allocating a unique blockchain ID is Product_ID = Hash (Product_Info), where Product_ID is the product blockchain ID, Product_Info is the product registration information, and Hash is a hash function used to generate a unique identifier; Supply chain information entry: In the supply chain of fresh food, each link will enter relevant information into the blockchain platform. The entry logic formula is Supply_Chain_Data = {Step1_Data, Step2_Data, ..., StepN_Data}, where Supply_Chain_Data is the supply chain information set, and Step1_Data, Step2_Data, ..., StepN_Data are the information of each link of the supply chain respectively; Information verification and storage: After the supply chain information is entered, the nodes in the blockchain network will verify the information. After the verification is passed, the information will be stored on the blockchain to form an unalterable historical record. The verification logic formula is Verified_Data = Validate (Supply_Chain_Data), where Verified_Data is the verified supply chain information, and Validate is a verification function used to check the authenticity and accuracy of the information; Information query and tracking: Consumers or related parties can query the complete supply chain information of the product on the blockchain platform by scanning the QR code on the product or entering the blockchain ID. The query logic formula is Query_Result = Query(Product_ID), where Query_Result is the query result and Query is the query function, which is used to obtain supply chain information based on the product blockchain ID.

6. The intelligent logistics supply chain management system according to claim 1, characterized in that: The collaborative management platform includes a procurement management module, a warehousing management module, a transportation management module, a sales management module and a data analysis and decision support module. The procurement management module is responsible for the formulation and execution of procurement plans, the warehousing management module is responsible for real-time monitoring and management of inventory, the transportation management module is responsible for the formulation and execution of transportation plans, and real-time tracking of transportation progress and cargo status, the sales management module is responsible for real-time monitoring and analysis of sales data, and provides sales forecasts and market demand analysis, the data analysis and decision support module is responsible for analyzing and mining supply chain data, and using random forests to predict future sales trends and inventory demand changes based on historical sales data and market trend information, while combining genetic algorithms to optimize inventory levels, reordering strategies, sales strategies and promotion activity plans to minimize inventory costs and meet sales needs.

7. An intelligent logistics supply chain management system according to claim 6, characterized in that: The specific steps of using random forest to predict future sales trends and inventory demand changes are as follows: Data preparation: Collect historical sales data and market trend information; Data preprocessing: clean historical sales data, remove outliers and missing values, and quantify market trend information; Constructing a random forest model: Using decision trees as base learners, construct multiple decision trees to form a random forest. Multiple sample sets are extracted from the training set through sampling with replacement to train each decision tree. When each node is split, some attributes are randomly selected for splitting. Model training and prediction: Use historical sales data and market trend information as input to train the random forest model, and use the trained model to predict future sales trends and inventory demand changes.

8. An intelligent logistics supply chain management system according to claim 6, characterized in that: The method of optimizing inventory levels, reordering strategies, sales strategies, and promotional activity plans by combining genetic algorithms includes the following steps: Define optimization goals: minimize inventory costs and meet sales needs; Encoding and initialization: Encoding parameters, including inventory levels, reorder points, sales strategies, and promotion activity plans, and initializing a population containing multiple different parameter combinations; Fitness function design: According to the optimization goal, a fitness function is designed to evaluate the pros and cons of each parameter combination scheme; Genetic operations: Selection: According to the fitness function value, select individuals with higher fitness as parents to generate the next generation; Crossover: Perform crossover operations on parent individuals to generate new offspring individuals; Mutation: Perform mutation operations on offspring individuals; Iterative optimization: Repeat the selection, crossover and mutation operations to generate a new population, and continuously screen out better parameter combinations according to the fitness function value until the predetermined number of iterations is reached or the fitness function value no longer increases significantly.

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