An effective method for solving multiple travelling salesman problem based on NSGA-II

• Main Authors: Yang Shuai, Shao Yunfeng, Zhang Kai
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2019-11-01
• Series: Systems Science & Control Engineering
• Subjects: multi-objective evolutionary algorithm; multiple travelling salesman problem; nsga-ii
• Online Access: http://dx.doi.org/10.1080/21642583.2019.1674220

In this paper, an effective multi-objective evolutionary algorithm is proposed to solve the multiple travelling salesman problem. In order to obtain minimum total visited distance and minimum range between all salesmen, some novel representation, crossover and mutation operators are designed to enhance the local and global search behaviours, then NSGA-II framework is applied to find well-convergent and well-diversity non-dominated solutions. The proposed algorithm is compared with several state-of-the-art approaches, and the comparison results show the proposed algorithm is effective and efficient to solve the multiple travelling salesman problems.