Multi-modal multi-objective traveling salesman problem and its evolutionary optimizer

Y. Liu1; L. Xu1; Y. Han2; N. Masuyama3; Y. Nojima3; H. Ishibuchi4; G. G. Yen5

10.1109/SMC52423.2021.9658818

2021

Proc. of 2021 IEEE International Conference on Systems, Man, and Cybernetics

1062-922X

978-1-6654-4208-4

2021 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)

770-777

October 17-20, 2021

Melbourne, Australia

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

A multi-modal multi-objective optimization problem (MMOP) may have equivalent Pareto optimal solutions. These solutions are different in the decision space but correspond to the same objective vector. Searching for equivalent Pareto optimal solutions with evolutionary algorithms is a hot topic in recent years. However, most existing researches are about continuous MMOPs, whereas there are few studies on discrete MMOPs. In this paper, we discuss the property of the multi-modal multi-objective traveling salesman problem and present a set of test problems. Then, we propose an evolutionary optimizer to solve the problem. Experimental results show that our evolutionary optimizer can find more equivalent Pareto optimal solutions than traditional multi-objective evolutionary optimizers on the test problems.

Conferences Evolutionary computation Pareto optimization Traveling salesman problems Search problems Optimization Cybernetics

其他

英语

CPCI-S ; EI

Fundamental Research Funds for the Central Universities[531118010537]

Computer Science

Computer Science, Cybernetics ; Computer Science, Information Systems

WOS:000800532000119

20220711616873

Evolutionary algorithms ; Multiobjective optimization ; Optimal systems ; Traveling salesman problem ; Vector spaces

Operations Research:912.3 ; Mathematics:921 ; Optimization Techniques:921.5 ; Systems Science:961

人工提交

1.Hunan University
2.Liaocheng University
3.Osaka Prefecture University
4.Southern University of Science and Technology
5.Oklahoma

Y. Liu,L. Xu,Y. Han,et al. Multi-modal multi-objective traveling salesman problem and its evolutionary optimizer[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2021:770-777.