A Many-Objective Evolutionary Algorithm with Spatial Division and Angle Culling Strategy  

作　　者：WANG Hongbo YANG Fan TIAN Kena TU Xuyan 

机构地区：[1]School of Computer and Communication Engineering,Beijing Key Lab.of Knowledge Engineering for Materials Science,University of Science and Technology Beijing,Beijing 100083,China

出　　处：《Chinese Journal of Electronics》2021年第3期437-443,共7页电子学报（英文版）

基　　金：the National Natural Science Foundation of China(No.61572074);National Key Research and Development Program of China(No.2020YFB1712104).

摘　　要：In a specific project,how to find a reasonable balance between a plurality of objectives and their optimal solutions has always been an important aspect for researchers.As a trade off between fast convergence and a rich diversity,a Many-objective evolutionary algorithm based on a spatial division and angle-culling strategy(MaOEA-SDAC)is proposed.In the reorganization stage,a restricted matching selection can enhance the reproductivity.In the environment selection stage,a space division and angle-based elimination strategy can effectively improve the convergence and diversity imbalance of its solution set.Through detailed experiments and a comparative analysis of the proposed MaOEA-SDAC with five other state-of-the-art algorithms on classical benchmark problems,the effectiveness of MaOEA-SDAC in solving high-dimensional optimization problems has been verified.

关 键 词：Many-objective optimization Spatial division Angle culling strategy Evolutionary algorithm 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]