文献类型：期刊文献

英文题名：A two-stage adaptive reference direction guided evolutionary algorithm with modified dominance relation for many-objective optimization

作者：Wang, Xuewu[1];Xie, Zuhong[1];Zhou, Xin[2];Gu, Xinsheng[1]

机构：[1]East China Univ Sci & Technol, Key Lab Adv Control, Optimizat Chem Proc Minist Educ, Shanghai 200237, Peoples R China;[2]Shanghai Univ Elect Power, Coll Automation Engn, Shanghai 200090, Peoples R China

年份：2023

卷号：78

外文期刊名：SWARM AND EVOLUTIONARY COMPUTATION

收录：;EI(收录号：20230813615384);WOS:【SCI-EXPANDED(收录号:WOS:000944921200001)】；

基金：This work is supported by the National Natural Science Foundation of China (No. 62076095, 61973120) .

语种：英文

外文关键词：Many-objective optimization; Irregular Pareto fronts APA; Dominance relation; Reference point self-adaption

摘要：Traditional dominance-based multi-objective evolutionary algorithms cease to be effective as the number of objectives increases due to the non-dominated sorting mechanism. Accordingly, a novel clustering indicator founded on the penalty-based adaptive rectangular area (APA) between solution and reference direction is proposed to assist in non-dominated levels sorting to deal with this issue. However, directly predefined reference directions with uniform distribution usually cause deteriorated performance in solving multi-objective problems with irregular Pareto fronts. Thus, an adaptive adjustment method guided by the local population is implemented in this paper. At this rate, a two-stage adaptive reference point guided evolutionary algorithm with APA-based dominance relation for many-objective optimization problems (named AREA-APA) is proposed and tested for solving these multi-objective optimization problems (including constrained and unconstrained problems). The proposed algorithm is proven to achieve comparable performance on scalable benchmark problems compared with state-of-the-art algorithms.