文献类型：期刊文献

英文题名：A fuzzy constraint handling technique for decomposition-based constrained multi- and many-objective optimization

作者：Han, Dong[1];Du, Wenli[1];Jin, Yaochu[2,3];Du, Wei[1];Yu, Guo[1]

机构：[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[2]Univ Surrey, Dept Comp Sci, Guildford GU2 7XH, Surrey, England;[3]Bielefeld Univ, Fac Technol, D-33619 Bielefeld, Germany

年份：2022

卷号：597

起止页码：318

外文期刊名：INFORMATION SCIENCES

收录：;EI(收录号：20221311836953);WOS:【SCI-EXPANDED(收录号:WOS:000792806800003)】；

基金：This work was supported by National Natural Science Foundation of China (Basic Science Center Program: 61988101) , National Natural Science Fund for Distinguished Young Scholars (61725301) , International (Regional) Cooperation and Exchange Project (61720106008) , and National Natural Science Foundation of China (62103150) .

语种：英文

外文关键词：Constrained multi-objective optimization; Evolutionary algorithm; Constraint handling technique; Fuzzy set

摘要：The challenge in solving constrained multi-objective optimization problems (CMOPs) is how to balance minimizing objectives and satisfying constraints, especially when the infeasible region is very large. To address this issue, this work proposes a fuzzy constraint handling technique, which uses the fuzzy set theory to accurately characterize the differ-ence between solutions on objective function values and constraint violation degrees. On this basis, a new concept, called "fuzzy advantage", is introduced to comprehensively quantify the degree to which one solution is better than others, allowing the infeasible solutions with promising fitness to survive. The proposed method is integrated with a decomposition-based multi-objective evolutionary algorithm to verify its effectiveness. Compared with nine state-of-the-art MOEAs on a number of test problems and a real -world optimization problem, the proposed algorithm shows high competitiveness in solv -ing a variety of CMOPs.(c) 2022 Published by Elsevier Inc.