交通阻塞条件下路线限制约束下配送优化的遗传算法

N. Mouttaki, J. Benhra, G. Rguiga
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引用次数: 1

摘要

摘要旅行推销员问题(TSP)是组合优化中的一个经典问题,它包括寻找穿越所有城市的最短路线,使得推销员只访问每个城市一次并返回起始城市。遗传算法是求解旅行商问题TSP的有效方法之一。目前的遗传算法的目的是在求解TSP时考虑遗传算法执行过程中发生的约束,例如交通堵塞。这个程序有两个重要贡献。第一个是提出一个简单的方法,考虑到与交通堵塞有关的不方便的路线。二是在初始化阶段采用接近策略,可以加快算法的执行速度。实验结果表明,改进后的算法比其他算法效果更好。结语部分是分析的结语,并提出建议和今后的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GENETIC ALGORITHM FOR OPTIMIZING DISTRIBUTION WITH ROUTE RESTRICTION CONSTRAINT DUE TO TRAFFIC JAMS
Abstract. The Travelling Salesman Problem (TSP) is a classical problem in combinatorial optimization that consists of finding the shortest tour through all cities such that the salesman visits each city only one time and returns to the starting city. Genetic algorithm is one of the powerful ways to solve problems of traveling salesman problem TSP. The current genetic algorithm aims to take in consideration the constraints happening during the execution of genetic algorithm, such as traffic jams when solving TSP. This program has two important contributions. First one is proposing simple method into taking in consideration an inconvenient route linked to traffic jams. The second one is the use of closeness strategy during the initialization step, which can accelerate the execution time of the algorithm. The results of the experiments show that the improved algorithm works better than some other algorithms. The conclusion ends the analysis with recommendations and future works.
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