Intelligent Warehouse Management System Research Articles

Optimization Algorithm of Intelligent Warehouse Management System Based on Reinforcement Learning

An Intelligent Warehouse Management System (IWMS) represents a technological leap forward in the realm of logistics and supply chain management. This sophisticated system integrates a suite of cutting-edge technologies, including artificial intelligence, machine learning, and the Internet of Things, to revolutionize the way warehouses operate. The primary focus is on the construction and performance evaluation of a robust big data prediction model within a cloud computing environment. The advent of big data and cloud computing has revolutionized the field of Logistics, offering immense potential for advanced data analysis and prediction. This research presents the development and evaluation of a robust prediction model for IWMS in Logistics applications. The proposed model incorporation of Reliable Discrete Variable Topology (RDVT) into the prediction model. RDVT introduces a topological data structure that enhances data reliability and ensures the integrity of Logistics information. The construction and training of the prediction model are meticulously detailed, encompassing data preprocessing, feature extraction, clustering, classification, and model evaluation. Additionally, the integration of fuzzy clustering with a reinforcement learning algorithm enhances the model's ability to handle uncertainty and imprecision in logistics management data. The advancement of Logistics in warehouses introduces the Reliable Discrete Variable Topology (RDVT) and a big data prediction model based on fuzzy clustering with a reinforcement learning algorithm in a cloud computing environment. The model's performance is rigorously assessed through extensive experimentation, including accuracy, precision, recall, and F1-score measurements.

Retracted: Design of Logistics Intelligent Warehouse Management System Based on Radio Frequency Identification Technology for 5G

Retracted: Design of Logistics Intelligent Warehouse Management System Based on Radio Frequency Identification Technology for 5G

Design of Logistics Intelligent Warehouse Management System Based on Radio Frequency Identification Technology for 5G

At present, the operation energy consumption of intelligent logistics warehouse management system based on B/S is too large, and the operation efficiency is low. In order to improve this situation, a design method of intelligent logistics warehouse management system based on radio frequency identification technology is proposed to optimize the hardware structure of the system. Based on the overall structure of the system, the network topology of the warehouse management system is divided into physical level, network level, data level, and application level. Further optimize the function and operation of the system software based on RFID technology, transfer the goods to the warehouse by logistics, count the goods, determine the goods location in the warehouse management system in the outbound management procedure, and collect the internal data of outbound goods through the RFID reader. Use the handling tools to transfer the picked goods to the warehouse out. The user management module mainly controls user login and user management. The statistical management of inventory is to clear and count the goods, which can provide a basis for the research in the field of intelligent logistics warehousing.

Design and implementation of a new intelligent warehouse management system based on MySQL database technology

In order to improve the material management level of enterprises, based on MySQL database technology, this paper makes an overall design of the warehouse management system, builds a MySQL database, and realizes the design and application of a new intelligent warehouse management system. Through the operation and test of the system, the results show that the system mainly realizes the five necessary functional modules of warehouse management: basic information management, system management, procurement management, warehousing management and inventory management. In the test, the system runs normally, the unit test and integration test can meet the expected requirements, realize the functions required by the user, and get the desired results within the user's acceptable response time (within 3S). It can provide automatic and comprehensive records for the whole process of material management of the enterprise, and provide real-time and correct information for all warehouse activities, resources and inventory levels.

Development of a Group Decision Support System with the Multi-Stage Multi-Attribute Group Decision Making (MS-MAGDM) Method on the Intelligent Warehouse Management System

Purpose: to find a solution with MS-DAGDM for the problem of different criteria used by decision maker at each stage.Design/methodology/approach: This research was conducted using literature review with a study of the theory of decision-making methods, group decisions, suplier selection processes, and factors that influence decisions in the context of warehousing and MS-MAGDM to solve the problems.Findings/result: This research find that GDSS prototypes which have four methods in making decisions. First, Analytical Hierarchy Process for weighting the division head level. Second, TOPSIS for divison head level decisions. Third, Hybrid Weight Averaging (HWA) manager level. Fourth, Time Weight Averaging (TWA) for manager level decisions.Originality/value/state of the art:The decision-making model of the GDSS system in this study combines four methods at each level of management. The section head level uses AHP for the level weighting and TOPSIS for decision making. Level managers use Hybrid Weight Averaging (HWA) weighting and Time Weight Averaging (TWA) for decisions. The combination of these methods is carried out using a Poisson distribution, for HWA and TWA operators to combine individual decisions into group decisions. Tujuan: Fokus penelitian ini adalah mencari solusi dengan MS-MAGDM untuk permasalahan perbedaan kriteria yang dipergunakan pembuat keputusan dalam setiap stage.Perancangan/metode/pendekatan: Metode yang digunakan yaitu kajian kepustakaan dengan kajian terhadap teori metode pembuatan keputusan, keputusan kelompok, proses pemilihan supplier, dan faktor yang berpengaruh pada keputusan dalam konteks pergudangan serta MS-MAGDM untuk menyelesaikan permasalahan tersebut.Hasil: Hasil penelitian ini berupa purwarupa GDSS yang memiliki 4 metode dalam pembuatan keputusan yaitu Analytical Hierarchi Process (AHP) untuk pembobotan level kepala bagian, TOPSIS untuk keputusan level kepala bagian, Hybrid Weight Averaging (HWA) pembobotan pada level manager dan Time Weight Averaging (TWA) untuk keputusan level managerKeaslian/ state of the art:Model pengambilan keputusan sistem GDSS penelitian ini menggabungkan 4 metode pada setiap tingkatan manajemen. Level kepala bagian menggunakan AHP untuk pembobotan level dan TOPSIS untuk pembuatan keputusan. Level manager menggunakan Hybrid Weight Averaging (HWA) pembobotan dan Time Weight Averaging (TWA) untuk keputusan. Penggabungan metode dilakukan menggunakan distribusi Poisson, untuk operator HWA dan TWA guna memadukan keputusan individu mejadi keputusan kelompok.

Design of Intelligent Warehouse Management System Based on MVC

Abstract Aiming at the problems of single function, low service level and difficult to meet customers’ demand for warehousing business in warehouse management system, a collaborative filtering recommendation algorithm is proposed. The algorithm calculates the similarity between items by analyzing user’s consumption behavior records, finds similar items to ‘target user’s favorite items, recommends similar items to ‘target user’, and designs commodity recommendation function for customer preferences, so as to improve user satisfaction and commodity sales efficiency. In order to provide users with better service experience and make the system operators easy to use, it is proposed to use B / S architecture and MVC framework model to design four modules : user management, allocation management, warehouse information management and report management, and to establish the corresponding database for unified management. Finally, the intelligent warehouse management system with high user experience satisfaction and convenient background management operation is obtained.

Visualisation technology in digital intelligent warehouse management system

This study introduces visualisation technology into digital intelligent warehouse management, combines Radio Frequency Identification (RFID) technology and Web Geographic Information System (GIS) technology, proposes software architecture, designs database and finally designs a set of intelligent warehouse management system based on visualisation technology. Through the pressure and performance test of the system, it is found that the user's waiting time is shorter, the system performance is stable and the designed system can meet the needs of business operations. By comparing the cost and time of goods storage management in one week, the results show that the system can reduce the cost of storage management by up to 40.3%, reduce the time of management by nearly half, and greatly improve the management efficiency. At the same time, due to the use of intelligent information tools, it can also reduce the mistakes caused by manual operation, improve the competitiveness of enterprises.

Artificially Intelligent Warehouse Management System

Artificially Intelligent Warehouse Management System

Development of intelligent warehouse management system based on Internet of things technology

With the development of electric power enterprises, the types and quantity of storage management materials are also increasing. With the rapid increase of warehousing frequency, warehousing management is very complex and diversified. The traditional manual warehouse operation mode has been difficult to meet the rapid storage management, which will seriously affect the operation efficiency of enterprises. By improving the intelligent warehouse management system, we must use RFID application technology, visualization technology, etc., which will improve the efficiency of material management. By reducing the cost of material management, we will achieve the optimal management of warehouse materials. Firstly, this paper analyzes the development trend of storage management and RFID technology. Then, the whole idea of system design is established.

Upgrading of Intelligent Warehouse Management System Based on RFID Technology- Taking Company as an Example

Upgrading of Intelligent Warehouse Management System Based on RFID Technology- Taking Company as an Example

Design of Intelligent Warehouse Management System

With the continuous development and application of information technology in the logistics industry, mobile applications, bar code, wireless communication, system integration and other technologies are widely used in warehouse management. Focusing on warehousing process management has become a new trend of informatization and lean management of material warehouse management. In this paper, the management of distributed storage cloud model is discussed, and a variety of automation, intelligence and information technology are utilized to effectively integrate the resources effectively. The author studies the resource scheduling optimization problem in the system, proposes an effective scheduling method, and initially realizes the intelligent warehouse management system based on cloud model, which provides users with a good package management service.

Research on the Intelligent Warehouse Management System Based on Near Field Communication (NFC) Technology

With the continuous development of retail and logistics, enterprise inventory management has become more and more complex, the traditional management mode can't meet the requirements of modern enterprise inventory management. In the environment of Internet of things, a kind of intelligent warehouse management system based on NFC is studied, which can realize the real time intelligent management of logistics. This paper design the NFC tags to store the warehouse information, freight car information, superior management order, etc., and read it by a smart android mobile terminal which support NFC, then through the communication network to transmit data information, to achieve NFC tag registration, data acquisition, content input, real-time data upload by scanning card, record management, query statistics and analysis report, which is an intelligent warehouse management system. It meets the requirements of modern logistics management, create more economic benefits for the enterprise, and has great realistic significance to promote the economic development of the logistics industry.

Research on Design and Implementation of Intelligent Warehouse Management System in Z Company

This paper aims at the practical problems of warehouse in Z enterprise, constructing the intelligent storage system, through the use of RFID technology, sensor technology, ZigBee technology to improve information transmission efficiency of the system, shortening the system response time. The paper solved the problem which the warehousing activities can’t be real-time controlled in the drawbacks of the product information in the warehouse.

Instruments Warehouse Management System in Power Industry Based on Sensor Networks

By employing sensor technology, control and network communication technology, we develop an intelligent instrument warehouse management system (IWMS) oriented to a typical instrument warehouse in power industry. We develop, test and improve the control hardware module, the instrument status indication module and the related software program. We also make the operational processes, provide a visual and intuitive operator interface, and realize and optimize the functions such as account management, query, breakdown alert and repair report. The implementation in Dongguan Power Supply Bureau reveals that IWMS optimizes the check-in and check-out process for the instruments, shortens the registration time, achieves the goal of automatic statistics, and improves the efficiency for instrument management and the operation productivity.

Agent-supported simulation environment for intelligent manufacturing and warehouse management systems

The manufacturing field is an area where the application of simulation is an essential tool for validating methods and architectures before applying them on the factory floor and the warehouse control. Multiagent system technology has demonstrated its utility in manufacturing system modelling and implementation. Agenthood features such as proactivity, reactivity, sociability and trust may also be useful for associating them with the specific simulation needs of the new manufacturing and warehouse management requirements. In this article, we present an agent-supported simulation tool for an intelligent manufacturing system and its influence with the management of the warehouse applied to a metal-mechanic manufacturing enterprise. The main goal is to provide a flexible simulation tool that can be adapted to solve the new manufacturing requirements and optimise and validate methods of management of material in warehouses that appear in real environments. Thus, the benefits of the multiagent theory application for the simulation of intelligent manufacturing and warehouse management system allows the experts of manufacturing domains to optimise the resource usage, control of inventory, providers and to have enough data to make decisions that influence the production level are presented.