32 results about "Logistic management" patented technology

This invention discloses a collaborative management method and system for the entire warehousing and logistics process, belonging to the field of warehousing and logistics information technology. Addressing the technical shortcomings of existing warehousing and logistics management, such as low inventory accuracy, poor scheduling efficiency, lagging information collaboration, and insufficient cost control, this invention integrates the entire process of inbound, storage, picking, outbound, transportation, and traceability, constructing a closed-loop management system of "data perception - algorithm decision-making - process collaboration - dynamic optimization." Through multi-dimensional data collection, optimized algorithm scheduling, cross-system data collaboration, and full-process traceability technology, this invention achieves precise inventory control, optimized logistics route planning, and efficient resource allocation, significantly improving warehousing and logistics operational efficiency, reducing overall costs, and enhancing management transparency. It is applicable to the digital management needs of warehousing and logistics in various industries, including manufacturing, retail, and e-commerce.

The present application relates to the technical field of logistics management, in particular to an integrated logistics management method of intelligent cloud warehouse system and physical warehouse, the present application punches through cloud warehouse, WMS, ERP, TMS and equipment metadata without modification, and generates the optimal "cloud-warehouse-line" operation package in seconds; edge reinforcement learning produces in 50 milliseconds, inventory difference is automatically reviewed and corrected, the accuracy is 99.9%; abnormal cargo location is recalculated in seconds, operation is optimized side by side; blockchain green identity card is traced throughout the process. Real-time early warning of transportation deviation, automatic reissue of nearby warehouse, time limit improvement of 30%, difference rate less than 0.1%, abnormal minute-level closed loop, system self-evolution, low cost, high efficiency, green and sustainable.

This invention relates to the field of logistics management technology, and specifically discloses a multi-entity logistics integrated management platform supporting dynamic resource scheduling. The method includes: an acquisition module for acquiring platform basic data, platform transaction data, and transaction link data; a determination module for determining the link type label, order node sequence, set of entities to be matched, and candidate entity set for each entity label in the set of entities to be matched for each transaction order in the platform transaction data; a link module for determining the link transaction data of multiple link transactions; a calculation module for calculating the scheduling value of each candidate matching entity set for each link transaction; and a management module for implementing execution management of all transaction orders in the platform transaction data. This allows for intelligent matching and dynamic optimization of multi-entity resources, improving the link integration efficiency, entity matching accuracy, and resource utilization efficiency of logistics transactions, and strengthening the platform's adaptability to complex logistics scenarios and its full-process control capabilities.

The utility model provides a kind of cloud label for logistics box, including shell and detection circuit, shell includes bottom shell and top cover, support piece two is equipped in top cover inner wall, one side of support piece two is installed in top cover side wall, and the other side lower part is equipped with clamping groove;Detection circuit includes circuit board assembly, temperature and humidity sensor, inclination sensor, vibration sensor, battery, power control module, data storage module;PCB is integrated with control chip and communication module on board;Control chip respectively with temperature and humidity sensor, inclination sensor, vibration sensor, power control module and data storage module carry out information interaction;The side wall of shell is equipped with and peripheral interface.This utility model integrates multiple high-precision sensors, can monitor the temperature and humidity, inclination state and vibration condition of logistics box in real time, provides comprehensive and accurate state information for logistics management.Communication module is provided simultaneously, ensures that data is stably and efficiently transmitted to cloud server, improves the real-time performance and reliability of logistics monitoring.

The present application relates to the technical field of intelligent logistics management, and more particularly to a steel intelligent logistics management system, which comprises a collection module, a determination module, a separation module, an analysis module and an adjustment module. The present application adopts a full-process intelligent architecture with the cooperative operation of the collection module, the determination module, the separation module, the analysis module and the adjustment module, combines real-time perception of multi-source data, multi-parameter fusion early warning, accurate separation of direction and path, contribution quantification and attribution, and scene-specific active regulation, realizes closed-loop management of risk identification, path positioning, cause diagnosis and active prevention and control in steel component transportation, ensures accurate fitting of the hanging angle through quantification of contribution and determination of abnormal dominant factors, promotes the transformation of the system from passive response to active and accurate prevention and control, reduces the risk of steel damage, and effectively solves the problems of inability to respond to dynamic working conditions in real time, abnormal continuous accumulation and poor multi-scene adaptability caused by manual adjustment lag, fixed adjustment range and lack of closed-loop control.

This application proposes a logistics management method and system for multimodal transport, belonging to the field of logistics management. The method includes: identifying intermodal transport information handover node pairs based on the multimodal transport logistics task; collecting fragmented logistics information sets from the intermodal transport information sender based on the target goods; establishing an information completeness index threshold based on the intermodal transport information receiver; performing predictive analysis on the fragmented logistics information set to obtain an information completeness prediction index; analyzing the information completeness index threshold and the information completeness prediction index based on a multi-condition triggering mechanism to generate intermodal transport information handover instructions; and executing the fragmented logistics information handover between intermodal transport information handover node pairs according to the handover instructions. The method intelligently determines the timing of information handover and ensures the completeness of the handedover information through information completeness prediction and a multi-condition triggering mechanism.

This invention discloses an automated storage and retrieval system (AS / RS) inbound and outbound control method for high-speed wire rods, relating to the field of logistics management technology. This method includes S1 preliminary preparation, system setup and warehouse deployment; S2 inbound control process, precise categorized inbound storage; S3 outbound control process, efficient on-demand delivery; S4 abnormal situation handling process; and S5 full-process information synchronization mechanism. This method achieves precise lifting and reduces damage: addressing the pain points of traditional methods such as difficult grasping and easy collisions, it employs machine vision 3D reconstruction and visual feedback closed-loop positioning technology to achieve precise "hand-eye coordination" grasping. Combined with intelligent anti-sway control, it avoids shaking during lifting, reducing product damage by 2000 tons annually and significantly improving product quality.

This disclosure relates to a warehouse logistics management method, a warehouse logistics management device, a storage medium, and a warehouse logistics management system. The warehouse logistics management method includes: acquiring logistics orders received by the warehouse within a predetermined time period; adjusting the location and quantity of buffer stations in the warehouse based on the order volume, type of goods shipped, and shipping frequency generated by the logistics orders; ensuring that the order volume includes at least the quantity of goods of each type; and shipping the goods according to the buffer stations in the warehouse. In this application, buffer stations are set at the front end of the container line to prevent the return of zero-pickup pallets after the documents are shipped out. The location and quantity of buffer stations in the warehouse are rationally adjusted based on the order volume, type of goods shipped, and shipping frequency generated by the logistics orders, resulting in the most reasonable and effective setting of the location and quantity of buffer stations, thereby maximizing shipping efficiency.

This invention discloses an intelligent logistics management system and optimization method, relating to the field of logistics supply chain management technology. Specifically, it includes an order management module, a warehouse management module, a delivery management module, a route optimization module, and an AI prediction module. This invention constructs a logistics information platform based on the fusion of multi-source heterogeneous data to achieve real-time monitoring and dynamic scheduling of order, warehouse, and delivery processes. It employs big data analysis and route optimization algorithms to globally optimize transportation routes, load matching, and resource allocation, and combines AI prediction models to improve the accuracy of logistics demand prediction. This enables intelligent management and efficient operation of the entire process of order management, warehouse management, and delivery management, promoting the intelligent and automated development of the entire logistics system, significantly improving logistics operational efficiency, reducing transportation costs, maximizing customer satisfaction with logistics services, and supporting enterprises in enhancing their market competitiveness.

This invention discloses a logistics management system and method based on multi-dimensional parameters, belonging to the field of logistics management technology. It includes a logistics equipment data acquisition module, a data preprocessing module, an anomaly early warning module, an operation and maintenance decision module, and an execution control module, all connected in sequence via communication. The logistics equipment data acquisition module collects multi-dimensional real-time operating parameters within the logistics scenario. The data preprocessing module standardizes the collected parameters and outputs a standard parameter dataset. The anomaly early warning module identifies abnormal states of logistics equipment, calculates the anomaly level, and generates corresponding early warning signals. The operation and maintenance decision module matches and verifies these parameters to generate operation and maintenance strategies. The execution control module decomposes and issues control commands to the corresponding logistics equipment. Using this invention, intelligent closed-loop operation and maintenance of logistics equipment across the entire chain can be achieved, improving the accuracy of anomaly identification and the efficiency of operation and maintenance handling, while reducing logistics operation and maintenance costs and the risk of business interruption.

This invention relates to the field of logistics cost technology, and specifically discloses an intelligent logistics cost accounting and management method and system. The method includes: acquiring multi-source logistics data and performing data preprocessing to obtain a multi-source logistics dataset; constructing a mixed integer programming model with multiple logistics management objectives; acquiring the current logistics cost accounting scenario, selecting a fusion strategy to fuse preset optimization algorithms, generating a fusion optimization algorithm, dynamically solving the mixed integer programming model with multiple logistics management objectives, and determining the optimal logistics vehicle scheduling scheme and the optimal logistics transportation route; intelligently calculating the logistics cost of each logistics order, and generating intelligent logistics cost accounting data. This invention, by constructing a mixed integer programming model with multiple logistics management objectives and designing a fusion optimization algorithm, effectively realizes the synergy of logistics scheduling, logistics route planning, and logistics cost, ensuring the quality of logistics cost accounting and management.

The present application relates to the field of logistics management, and discloses a kind of processing method, device, equipment and storage medium of logistics data index, the method comprises: obtaining logistics data, and determining the data meaning of each index in logistics data and the business type corresponding to each index;Multiple indexes in logistics data are classified and processed, at least one data subject domain is obtained, and the mapping relationship between the index in each data subject domain and data subject domain is established;Each index in mapping relationship is hierarchically divided, and an index system is obtained;According to the index system, generate index white paper.The technical scheme provided by the present application processes the index in logistics data, forms an index system, and standardizes the management of the index in logistics data, and according to the formed index system, when data analysis, mass logistics data can be accurately and effectively processed and analyzed, and the efficiency and accuracy of data analysis are improved.

This invention belongs to the field of warehousing and logistics management technology, and relates to a high-speed electronic equipment inventory tracking system. It acquires inventory records of high-speed electronic equipment with unique serial numbers in real time, constructs a pool of consecutively numbered intervals isolated by equipment model and batch; responds to inbound, outbound, or transfer operation events, performs interval merging and interval splitting maintenance to update the available interval pool in real time; based on outbound requests, it filters available consecutively numbered intervals from the available interval pool that meet the cumulative available quantity requirements, and sorts the filtered available consecutively numbered intervals based on a priority recommendation rule of region identifier matching; after confirmation, the selected intervals are aggregated into a single outbound order and pre-locked. This invention can automatically combine fragmented intervals and proactively manage fragmentation, intelligently filter compatible equipment based on business attributes, and prevent concurrent conflicts through pre-locking, thus helping to improve the efficiency and accuracy of high-speed electronic equipment outbound operations.

This invention belongs to the field of warehousing and logistics management technology, specifically referring to an automated warehousing and logistics management system. The system includes a palletizing generation module, a refined scenario verification module, and a back-end logistics adaptive decision-making module. This solution utilizes a lightweight model without graphical rendering to verify the accessibility and collision-free nature of goods placement in real time. Through both lightweight and refined verification, backup candidate goods reduce the number of backtracking adjustments, and the optimal solution is output after iterative convergence, improving palletizing optimization efficiency and solution adaptability. The back-end logistics adaptive decision-making module constructs a dataset for the optimal path algorithm of the traveling salesman problem, collects warehouse layout data to classify layout types, gathers logistics requirements to obtain constraints, assigns weights according to layout matching and constraint matching, and automatically searches for suitable picking and scheduling strategies. This achieves precise matching between warehouse layout and logistics requirements, improving the efficiency and rationality of back-end logistics picking and scheduling.

1. Name of the product in this design: Logistics Management Box. 2. Purpose of this design: To classify and categorize logistics products. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

This invention relates to the field of intelligent interaction and logistics management technology, and discloses an intelligent logistics customer service question-and-answer method, apparatus, equipment, and medium, comprising: receiving a logistics inquiry request; identifying the user's inquiry intent and set of business elements in the logistics inquiry request; retrieving logistics nodes, business rules, and historical cases that match the user's inquiry intent and set of business elements; constructing a response framework for the logistics inquiry request; retrieving real-time logistics status data and generating candidate answers using the response framework; extracting intent type features from the user's inquiry intent and filtering priority determination elements from the set of business elements; determining the logistics business priority based on the priority determination elements; calculating a weighted score for each candidate answer based on the intent type features and the logistics business priority; and selecting the candidate answer with the highest weighted score as the target customer service answer. This invention can improve the accuracy of intelligent logistics customer service question-and-answer.

This invention provides a dual-database driven intelligent logistics sorting method and apparatus, belonging to the field of intelligent logistics management technology. The method includes: acquiring logistics management data and performing preprocessing and standardization to obtain standardized logistics management data; jointly extracting logistics entities and relationships from the standardized logistics management data and constructing a logistics knowledge graph using a graph database; extracting semantic features of each logistics entity and relationship in the logistics knowledge graph using a knowledge graph embedding method to obtain hidden feature vectors for each logistics entity and relationship, and storing them in a vector database; querying the vector database through similarity calculation to determine the physicochemical attribute classification result of the goods to be sorted; and performing logistics sorting on the goods to be sorted according to the physicochemical attribute classification result. This invention utilizes a dual-database driven approach of a graph database and a vector database, which can improve the efficiency of logistics acquisition, classification, and sorting.

The present application relates to the technical field of logistics inventory management, in particular to a kind of inventory logistics management method and system based on Internet of Things, method includes the following steps: obtaining the cargo information in logistics warehouse and the order information of customer;Cargo information and the order information of customer are associated and stored to cloud server;The order information board and cargo information board are obtained by dividing the region to cloud server, information line and selection chain are set in order information board, and the interactive connection between order information board and cargo information board is established;In response to receiving real-time order information, real-time order information is stored to order information board, and the cargo location information corresponding to the goods in order information is determined based on communication connection;Based on cargo location information, the goods in warehouse are managed, the efficiency and accuracy of warehouse operation can be improved, the corresponding order goods are positioned and extracted conveniently and quickly, the searching time is reduced, and the logistics efficiency is improved.

This invention relates to the field of logistics management technology, and more particularly to an intelligent calculation and dynamic optimization method for logistics park operation processes, comprising: calculating the changes in the overall equipment status, task progress, and vehicle queuing density respectively, and merging the changes into an operation status index; for each pending task, reading the corresponding task completion ratio and task queuing density, calculating the node process pressure index and task priority index, until the calculation of all pending tasks is completed, and constructing a task priority queue; for each task in the task priority queue, calculating the matching score between the task and the equipment, generating a task execution allocation table, and simultaneously updating the load status of the equipment through an update function to generate equipment status update values; reading the task execution allocation table, calculating the task adjustment index, re-evaluating the matching between tasks and equipment, and generating an optimized task execution allocation table and equipment status update values.

This application pertains to the field of logistics and distribution, specifically an intelligent logistics and distribution dispatch system. The system includes a terminal server comprising an order receiving module, a data analysis module, an intelligent dispatch module, a vehicle monitoring module, a route planning module, a communication module, and a user exchange module. The order receiving module receives logistics and distribution order information from e-commerce platforms, customer terminals, and other channels, including order number, shipping address, delivery address, cargo weight, volume, and delivery time requirements. After formatting the order information, it transmits it to the data analysis module, which analyzes and processes the received order information. This application features a reasonable design, achieving intelligent order processing and efficient vehicle dispatch through multi-module collaboration. Combined with an optimized design incorporating GPS positioning devices, it improves delivery efficiency, reduces costs, ensures stable equipment operation, and enhances customer and logistics management satisfaction.

This invention relates to the field of logistics management technology, specifically to a method, system, and storage medium for optimizing multimodal transport delivery routes. The method includes: generating individual solutions based on basic cargo transportation data to form an initial population; updating the initial population using a hybrid optimization algorithm based on a multi-objective constraint model; and obtaining the optimal individual solution from the initial population as the Pareto optimal solution set. The hybrid optimization algorithm employs an adaptive PSO-CS operator to update the initial population. The PSO operator updates the speed and position of individual solutions and, based on congestion, obtains the globally optimal individual solution as the offspring population. The CS operator, through adaptive scheduling decisions, performs global or local CS perturbations to fine-tune the obtained individual solutions, generating the offspring population. This scheme effectively handles the heterogeneous search space and complex constraints of MTOP, dynamically and adaptively refining the shrinkage speed, thus improving search efficiency and quality.

The application relates to the technical field of logistics management, and discloses a logistics management method and system based on a data middle station, which comprises the following steps: acquiring and standardizing order information, warehouse state, vehicle position, customer feedback and settlement data; establishing a hierarchical structure in the data middle station and extracting indexes such as transportation timeliness, warehouse turnover, delivery track deviation and customer feedback grade; comparing the indexes with historical data to generate abnormality detection results; when there is an abnormality, introducing multi-source information for consistency verification and generating a candidate path; sequentially screening the final scheduling path through a time threshold, resource carrying capacity and track consistency; combining customer feedback to generate a compensation factor to correct operation indexes during execution; when the abnormality still exists, triggering path reconstruction and resource reallocation; and finally generating and displaying graded early warning information. Through comparison and path screening, the application improves the abnormality identification accuracy and the reliability of logistics scheduling.

This invention discloses an integrated intelligent warehousing and distribution logistics management system, comprising: an intelligent warehousing module, a warehousing collaboration module, an intelligent distribution management module, a data analysis module, a decision support module, and a system management module. The intelligent warehousing collaboration module generates picking tasks based on orders and dynamically schedules AGVs to complete goods handling. The collaboration module maps the status of goods, equipment locations, and operational processes within the physical warehouse in real time. This invention has the following advantages: dynamic location allocation improves warehouse space utilization, shortens AGV task response time, predictive maintenance reduces equipment failure rates, unmanned delivery reduces last-mile delivery costs, knowledge graphs and AI algorithms automate routine problem handling, digital twins and large-screen visualization systems provide transparent management throughout the entire process, intelligent warehousing management enables rapid storage and retrieval of goods and accurate picking, and intelligent distribution management optimizes vehicle scheduling and route planning.

[Problem] To provide a logistics management system, a logistics management method, and a computer program that are capable of efficiently managing package information and being efficiently used together with a system for another purpose. [Solution] This logistics management system comprises: an input item storage unit that stores an input item set in advance for each package and each logistics base; an identification information setting unit that sets second identification information different from first identification information, which is set for a purpose different from logistics management, in association with a first code attached to the package; a redirecting unit that carries out redirection to a webpage corresponding to the second identification information; an information reception unit that receives package identification information and base identification information from a worker; a form output unit that extracts the input item corresponding to the package and the logistics base from the input item storage unit and outputs, to the worker, a form for inputting the extracted input item; an input unit that receives input information corresponding to the input item input by the worker; and a tracking database that stores the input information.

The utility model relates to the technical field of warehouse logistics management, especially to a warehouse-in and warehouse-out management intelligent terminal, multiple buffer structures effectively absorb drop impact, protect internal precision components, prolong equipment life, and the multi-degree-of-freedom adjustable data acquisition module makes the operator not need frequent large-scale adjustment terminal posture to aim at target label, reduces action amplitude and fatigue, and the ergonomic handle and counterweight design provide more comfortable, stable holding experience, the dirt-proof sealed screen and sliding dustproof cover ensure that the screen is clear and usable under the harsh environment, and the efficient forced heat dissipation air duct ensures that the equipment stably operates for a long time, avoids overheating failure, and the utility model significantly improves the durability, operation comfort, code scanning efficiency, heat dissipation performance, maintenance convenience and environmental adaptability of the terminal, and has outstanding practical value.

This invention discloses a method and system for monitoring the entire logistics process, relating to the field of logistics information technology. The method divides the monitor's status into four stages: ready for use, in use, ready for recycling, and in recycling, triggering data processing based on state transitions. The system acquires logistics information, equipment information, and location information, and accurately pushes data to the logistics management interface and user access interface through a dual-interface mechanism, ensuring information security. By combining energy reserves, power prediction, historical trajectory data, and electronic fence technology, it achieves intelligent monitoring and anomaly warnings for stages such as transportation stagnation and equipment recycling, improving the automation and closed-loop management level of logistics monitoring.

This invention discloses a closed-loop handling method for logistics anomalies, specifically relating to the field of multi-event collaborative decision-making and resource scheduling in logistics management. It addresses the problems of resource competition and low overall handling efficiency caused by independent handling of multiple concurrent anomalies in existing technologies. The method involves acquiring information on anomalies to be handled and shared resources, identifying groups of anomalies that may compete for the same resources; planning multiple handling paths for each event within a group and constructing a network of dependencies between paths; parallel deducing path combinations to identify mutually exclusive conflicts between solutions; generating and executing a globally optimal collaborative handling plan that coordinates all events; and finally collecting feedback on the handling results to update resource information, forming a closed-loop decision optimization mechanism. This achieves systematic collaborative handling and dynamic resource optimization for concurrent logistics anomalies.

The application relates to the technical field of logistics management, and discloses a supply chain multi-party coordination scheduling system based on cloud edge cooperation, which comprises a resource integration module, a same-source identification family module, a coordination information module, a coordination scheduling instruction module, a cooperation data link module and a coordination state certificate module; the resource integration module encapsulates supply end local operation data into real-time operation snapshots, and combines the local coordination identification to form a cooperative perception information set. The same-source identification family module obtains a same-source identification family through self-negotiation marking traceability. The coordination information module maps heterogeneous operation data to global information to obtain a global coordination information set. The coordination scheduling instruction module constructs a conflict relation graph and generates a coordination scheduling instruction set. The cooperation data link module disassembles the instruction into cooperation execution instructions and establishes a cooperation data link. The coordination state certificate module synchronizes the state and generates a coordination state certificate. The application can improve the efficiency of supply chain multi-party coordination scheduling based on cloud edge cooperation.

The application relates to the technical field of warehouse logistics management, in particular to a warehouse goods warehouse-in and warehouse-out management method and system. The method comprises the following steps: obtaining historical order data of warehousing; based on the historical order data weighted by a time decay function, calculating the weighted occurrence frequency of each commodity and the weighted co-occurrence frequency of a commodity pair to determine the correlation degree between the commodity pair; determining the adjacent storage value of the commodity pair according to the average value of the correlation degree between the commodity pair, the weighted co-occurrence frequency, the storage category and the weight difference; based on all available storage locations, the adjacent storage value of the commodity pair and the weighted occurrence frequency of each commodity, constructing an optimization model with the target of minimizing the total picking cost, solving the optimization model to obtain a storage location allocation scheme; and performing the warehouse-in and warehouse-out operation according to the storage location allocation scheme. The application can optimize the picking path and improve the warehousing operation efficiency by evaluating the commodity correlation and the physical constraint.

The application discloses a logistics management system development method based on service demand big data analysis, and relates to the technical field of logistics management.The application significantly improves the intelligent level and development efficiency of the logistics management system by constructing a full-link automatic development system.Firstly, ST-DBSCAN and KDE kernel density estimation algorithms are used for deep data cleaning and feature extraction, and a high-dimensional feature matrix generated by PCA dimension reduction is combined to accurately depict the space-time evolution law of the logistics network.Secondly, an LSTM and XGBoost stacked ensemble model is used to capture the time sequence dependence and static attribute coupling relationship, greatly reducing the MAPE and RMSE errors of resource demand prediction, and realizing accurate transport capacity prediction.The system can automatically generate a micro-service code framework and an HPA elastic scaling strategy based on the predicted peak value, realize adaptive adjustment of the architecture, and avoid resource waste and service overload.In summary, the application shortens the system development cycle and improves the system throughput and stability in a high-concurrency scenario.