期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2020
卷号：98
期号：24
页码：4014-4027
出版社：Journal of Theoretical and Applied
摘要：As a combinatorial optimization problem, the capacitated vehicle routing problem (CVRP) is a vital one in the domains of distribution, ransportation and logistics. Despite the fact that many researchers have solved the problem using a single objective, only little attention has been given to multi-objective optimization. As compared to multi-objectives, the comparison of solutions is easier with single-objective optimization fitness function. In this paper, the following objectives were achieved: (i) in view of the domain of the multi-objective CVRP, the total distance traveled by the vehicles and the total number of vehicles used are reduced, and (ii) in the view of the technique, a multi-objective Ant Colony System is proposed to solve the multi-objective of CVRP based on the experience of sub-paths. The proposed algorithm was evaluated using some standard benchmark problems of CVRP. The results show that the algorithm which has been proposed in this study is highly competitive and quite effective for multi-objective optimization of CVRP.
