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      Logistics Distribution Path Optimization Algorithm Based on Intelligent Management System

      research-article
      Computational Intelligence and Neuroscience
      Hindawi

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          Abstract

          There are three key points in logistics distribution: the distribution vehicle, the amount of goods, and the distribution path. Comprehensive calculation and optimization of these three parameters can plan a reasonable and efficient distribution scheme, especially the distribution path. This study aims to study the method of optimizing the logistics distribution path and strives to find the optimal distribution scheme and the shortest path, which can reduce the distribution error rate, distribution time, and labor costs, thus realizing intelligent management. In this study, intelligent management methods such as radio-frequency identification technology and ant colony algorithm are proposed to optimize the logistics distribution path and realize the safe and efficient logistics distribution. The experimental results of this study show that for the current logistics distribution, the RFID system has a positioning rate of close to 100% when the number of fixed points reaches about 300, and almost all accurate positioning is achieved. The ant colony algorithm can also accurately find the shortest distance after selecting appropriate parameters, which is about 200 meters away from the actual shortest distance.

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          Most cited references23

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          Trends in transportation and logistics

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            Digital twin and cloud-side-end collaboration for intelligent battery management system

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              • Article: not found

              Logistics service design for cross-border E-commerce using Kansei engineering with text-mining-based online content analysis

                Author and article information

                Contributors
                Journal
                Comput Intell Neurosci
                Comput Intell Neurosci
                cin
                Computational Intelligence and Neuroscience
                Hindawi
                1687-5265
                1687-5273
                2022
                26 September 2022
                : 2022
                : 3699990
                Affiliations
                School of Business, Jilin Business and Technology College, Changchun 130507, Jilin, China
                Author notes

                Academic Editor: Kapil Sharma

                Author information
                https://orcid.org/0000-0002-3230-9032
                Article
                10.1155/2022/3699990
                9529449
                0d23896a-af52-468e-9423-a97e36848fc1
                Copyright © 2022 Foshang Li.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 June 2022
                : 12 August 2022
                : 8 September 2022
                Categories
                Research Article

                Neurosciences
                Neurosciences

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