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Logistics Distribution Route Optimization Based on Genetic Algorithm
Aiming at the problem of logistic division based on genetic algorithm, it is planned to study the improvement of logistic distribution methods. We first meet the requirements of the genetic algorithm of logistic development, use the division method to divide the delivery area of the gene, and formul...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279064/ https://www.ncbi.nlm.nih.gov/pubmed/35845887 http://dx.doi.org/10.1155/2022/8468438 |
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author | Xin, Liu Xu, Peng Manyi, Gu |
author_facet | Xin, Liu Xu, Peng Manyi, Gu |
author_sort | Xin, Liu |
collection | PubMed |
description | Aiming at the problem of logistic division based on genetic algorithm, it is planned to study the improvement of logistic distribution methods. We first meet the requirements of the genetic algorithm of logistic development, use the division method to divide the delivery area of the gene, and formulate a functional delivery plan, which generally includes weight measurement, measurement time, customer value measurement, instrument measurement time, and the whole process index. We set weight goals and find the best way to improve genetic algorithm delivery. The experimental comparison results show that the optimal method takes less than 2 minutes to find the optimal method, while the normal process takes 4 minutes to find the optimal method, and the longest can reach 5 minutes. The comparison shows that the traditional algorithm takes longer to find the correct way than the algorithm developed this time. Finally, the simple logistic distribution optimization method model and the soft time-limited logistic distribution processing optimization model are calculated and simulated by the genetic testing algorithm and genetic algorithm development. The effectiveness of the improved genetic algorithm in local research and the effectiveness of the logistic transportation allocation solution are determined. |
format | Online Article Text |
id | pubmed-9279064 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-92790642022-07-14 Logistics Distribution Route Optimization Based on Genetic Algorithm Xin, Liu Xu, Peng Manyi, Gu Comput Intell Neurosci Research Article Aiming at the problem of logistic division based on genetic algorithm, it is planned to study the improvement of logistic distribution methods. We first meet the requirements of the genetic algorithm of logistic development, use the division method to divide the delivery area of the gene, and formulate a functional delivery plan, which generally includes weight measurement, measurement time, customer value measurement, instrument measurement time, and the whole process index. We set weight goals and find the best way to improve genetic algorithm delivery. The experimental comparison results show that the optimal method takes less than 2 minutes to find the optimal method, while the normal process takes 4 minutes to find the optimal method, and the longest can reach 5 minutes. The comparison shows that the traditional algorithm takes longer to find the correct way than the algorithm developed this time. Finally, the simple logistic distribution optimization method model and the soft time-limited logistic distribution processing optimization model are calculated and simulated by the genetic testing algorithm and genetic algorithm development. The effectiveness of the improved genetic algorithm in local research and the effectiveness of the logistic transportation allocation solution are determined. Hindawi 2022-07-06 /pmc/articles/PMC9279064/ /pubmed/35845887 http://dx.doi.org/10.1155/2022/8468438 Text en Copyright © 2022 Liu Xin et al. https://creativecommons.org/licenses/by/4.0/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. |
spellingShingle | Research Article Xin, Liu Xu, Peng Manyi, Gu Logistics Distribution Route Optimization Based on Genetic Algorithm |
title | Logistics Distribution Route Optimization Based on Genetic Algorithm |
title_full | Logistics Distribution Route Optimization Based on Genetic Algorithm |
title_fullStr | Logistics Distribution Route Optimization Based on Genetic Algorithm |
title_full_unstemmed | Logistics Distribution Route Optimization Based on Genetic Algorithm |
title_short | Logistics Distribution Route Optimization Based on Genetic Algorithm |
title_sort | logistics distribution route optimization based on genetic algorithm |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279064/ https://www.ncbi.nlm.nih.gov/pubmed/35845887 http://dx.doi.org/10.1155/2022/8468438 |
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