A Decomposition-based Large-scale Multi-modal Multi-objective optimization Algorithm

Peng，Yiming; Ishibuchi，Hisao

10.1109/CEC48606.2020.9185674

2020-07-01

IEEE Congress on Evolutionary Computation (CEC) as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

978-1-7281-6930-9

2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings

1-8

JUL 19-24, 2020

null,null,ELECTR NETWORK

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

IEEE

A multi-modal multi-objective optimization problem is a special kind of multi-objective optimization problem with multiple Pareto subsets. In this paper, we propose an efficient multi-modal multi-objective optimization algorithm based on the widely used MOEA/D algorithm. In our proposed algorithm, each weight vector has its own sub-population. With a clearing mechanism and a greedy removal strategy, our proposed algorithm can effectively preserve equivalent Pareto optimal solutions (i.e., different Pareto optimal solutions with same objective values). Experimental results show that our proposed algorithm can effectively preserve the diversity of solutions in the decision space when handling large-scale multi-modal multi-objective optimization problems.

diversity maintenance Evolutionary multi-objective optimization MOEA/D multimodal multi-objective optimization

第一

英语

EI ; CPCI-S

Guangdong Provincial Key Laboratory[2020B121201001] ; Program for Guangdong Introducing Innovative and Enterpreneurial Teams[2017ZT07X386] ; Shenzhen Science and Technology Program[KQTD2016112514355531] ; Program for University Key Laboratory of Guangdong Province[2017KSYS008]

Computer Science ; Engineering ; Mathematical & Computational Biology ; Operations Research & Management Science

Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Mathematical & Computational Biology ; Operations Research & Management Science

WOS:000703998201063

20204109316928

Pareto principle ; Optimal systems ; Evolutionary algorithms

Optimization Techniques:921.5 ; Systems Science:961

2-s2.0-85092064604

Scopus

Southern University of Science and Technology,Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation,Shenzhen,518055,China

Peng，Yiming,Ishibuchi，Hisao. A Decomposition-based Large-scale Multi-modal Multi-objective optimization Algorithm[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2020:1-8.