供应链视角下的城乡农产品物流配送最优路径规划

Q3 Computer Science

Informatica (Slovenia) Pub Date : 2023-05-23 DOI:10.31449/inf.v47i5.4557

Xiumei Wang, Xiaoli Song

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引用次数: 0

摘要

物流配送是农产品供应链的重要环节。本文利用自适应遗传算法对农产品配送中心与客户之间的配送路径进行了优化，并与贪心遗传算法和传统遗传算法进行了仿真比较。结果表明，尽管贪心算法获得路径规划方案的速度更快，但遗传算法获得的规划路径更好，自适应遗传算法比传统遗传算法获得更短的配送路径、更低的运输成本和更少的计算时间

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Optimal path planning of logistics distribution of urban and rural agricultural products from the perspective of supply chain

Logistics distribution is a crucial part of the supply chain of agricultural products. This paper optimized the distribution path of agricultural products between distribution centers and customers using the adaptive genetic algorithm and conducted a simulation comparison with greedy and traditional genetic algorithms. The results showed that although the greedy algorithm obtained the path planning scheme faster, the planning path obtained by the genetic algorithm was better, and the adaptive genetic algorithm obtained a shorter distribution path, lower transportation cost, and less computation time than the traditional genetic algorithm

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来源期刊

Informatica (Slovenia) Computer Science-Computer Science Applications

CiteScore

1.90

自引率

0.00%

发文量

期刊介绍： Informatica is an international refereed journal with its base in Europe. It has entered its 33th year of publication. It publishes papers addressing all issues of interests to computer professionals: from scientific and technical to educational, commercial and industrial. It also publishes critical examinations of existing publications, news about major practical achievements and innovations in the computer and information industry, as well as conference announcements and reports.