电子学报2017，Vol.45Issue(11)：2677-2684,8.DOI:10.3969/j.issn.0372-2112.2017.11.015
基于模糊C均值聚类的锦标赛选择机制与多目标优化研究
Tournament Selection for Multiobjective Optimization Based on Fuzzy C-Means Clustering Method
摘要
Abstract
A fuzzy C-means clustering based evolutionary algorithm called FCEA was proposed to optimize multiobjective optimization problems.In the process of iteration of this algorithm,a fuzzy C-means clustering method is firstly employed to implement a fuzzy partition of the population so as to discover the population distribution structure and to obtain a membership matrix of the population at each generation.According to the distribution structure,a membership based tournament selection strategy (MBTS) is designed to select neighboring solutions from the population for recombination and to guide search.The experiments present that MBTS significantly contributes to the performance of FCEA.Comparison experiments show that the proposed FCEA outperforms MOEA/D-DE,NSGAII,SPEA2 and SMS-EMOA on solving GLT test suite with complicated Pareto Front (PF) shapes.关键词
进化算法/多目标优化/模糊C均值聚类/隶属度选择Key words
evolutionary algorithm/multiobjective optimization/fuzzy C-means cluster/membership selection分类
信息技术与安全科学引用本文复制引用
张屹,余振,李子木,陆瞳瞳..基于模糊C均值聚类的锦标赛选择机制与多目标优化研究[J].电子学报,2017,45(11):2677-2684,8.基金项目
国家自然科学基金(No.71501110) （No.71501110）
