An improved genetic algorithm for the multiple traveling salesman problem

被引：5
|
作者：
Zhao, Fanggeng [1 ,2 ]
Dong, Jinyan [1 ]
Li, Sujian [2 ]
Yang, Xirui [1 ]
机构：
[1] Vehicle Management Inst, Dept Vehicle Management, Bengbu 233011, Peoples R China
[2] Beijing Univ Sci & Technol, Dept Logist Engn, Beijing 100083, Peoples R China
来源：
2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11 | 2008年
关键词：
Genetic Algorithm; Multiple Traveling Salesman Problem; Pheromone-based Crossover;
D O I：
10.1109/CCDC.2008.4597663
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, an improved genetic algorithm for the multiple traveling salesman problem was proposed. In the algorithm, a pheromone-based crossover operator is designed, and a local search procedure is used to act as the mutation operator. The pheromone-based crossover can utilize both the heuristic information, including edge lengths and adjacency relations, and pheromone to construct offspring. Experimental results for benchmark instances clearly show the superiority of our genetic algorithm.
引用
收藏
页码：1935 / 1939
页数：5
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