文献类型：期刊文献

英文题名：A constrained multiobjective evolutionary algorithm with the two-archive weak cooperation

作者：Li, Yingwei[1,2];Feng, Xiang[1,2];Yu, Huiqun[1,2]

机构：[1]East China Univ Sci & Technol, Dept Comp Sci & Engn, Shanghai 200237, Peoples R China;[2]Shanghai Engn Res Ctr Smart Energy, Shanghai 200237, Peoples R China

年份：2022

卷号：615

起止页码：415

外文期刊名：INFORMATION SCIENCES

收录：;EI(收录号：20224312995776);WOS:【SCI-EXPANDED(收录号:WOS:000877037400004)】；

基金：Acknowledgements This work is supported by the National Natural Science Foundation of China (No.62276097) , Key Program of National Nat- ural Science Foundation of China (No.62136003) , National Key Research and Development Program of China (No. 2020YFB1711700) , Special Fund for Information Development of Shanghai Economic and Information Commission (No. XX-XXFZ-02-20-2463) and Scientific Research Program of Shanghai Science and Technology Commission (No.21002411000) .

语种：英文

外文关键词：Two -archive weak cooperation; Constrained handling; Constrained multiobjective optimization; Evolutionary algorithm

摘要：The significant issue to solve constrained multiobjective optimization problems (CMOPs) is to keep the balance between objectives and constraints, but the existing evolutionary algorithms are in the face of challenges for solving CMOPs with complex feasible regions. Based on this purpose, a constrained multiobjective evolutionary algorithm with the two-archive weak cooperation (CMOEA-TWC) is proposed in this article. In CMOEA-TWC, two archives are evolved, which are denoted as driving archive and normal archive, respectively. Besides, the weak cooperation of two archives is designed for sharing valuable information between archives. Specifically, the driving archive only considers objectives, while the normal archive considers both objectives and constraints. In addition, the minimum shiftbased density estimation-based (SDE) distance is adopted to enhance the diversity of solutions in the driving archive, and a strict constrained dominance principle is designed to improve the feasibility of solutions in the normal archive. The proposed algorithm is tested on 47 CMOPs of 4 benchmark suites with the comparison of 4 state-of-the-art algorithms. The experimental results demonstrate that the average ranks in terms of inverted generational distance (IGD) outperform those of existing state-of-the-art competitors.(c) 2022 Published by Elsevier Inc.