New Genetic Algorithm for Min-Max Vehicle Routing Problem

被引:0
|
作者
Ren, Chunyu [1 ]
机构
[1] Heilongjiang Univ, Sch Informat Sci & Technol, Harbin 150080, Peoples R China
关键词
MMVRP; individual amount control; improved route crossover operation; choice strategy; new genetic algorithm; SEARCH;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Tailored to the individual demands and the diversified requirements in the real operation, this paper is focused on the min-max vehicle routing problem (MMVRP) to shorten the longest journey in the circuit. New genetic algorithm is used to get the optimization solution. First of all, use natural number coding so as to simplify the problem; apply insertion method so as to improve the feasibility of the solution. Secondly. use the individual amount control choice strategy so as to guard the diversity of group; apply improved route crossover operation to avoid destroying good gene parts. Finally, the good performance of improved algorithm can be proved by experiment calculation and concrete examples.
引用
收藏
页码:21 / 27
页数:7
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