δ-similar elimination to enhance search performance of multiobjective evolutionary algorithms

被引：0
|
作者：
Aguirre, Hernan [1 ]
Sato, Masahiko [1 ]
Tanaka, Kiyoshi [1 ]
机构：
[1] Shinshu Univ, Fac Engn, Nagano 3808553, Japan
来源：
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | 2008年 / E91D卷 / 04期
关键词：
multiobjective evolutionary algorithms; delta-similar elimination; controlled elitism; selection;
D O I：
10.1093/ietisy/e91-d.4.1206
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we propose delta-similar elimination to improve the search performance of multiobjective evolutionary algorithms in combinatorial optimization problems. This method eliminates similar individuals in objective space to fairly distribute selection among the different regions of the instantaneous Pareto front. We investigate four eliminating methods analyzing their effects using NSGA-II. In addition, we compare the search performance of NSGA-II enhanced by our method and NSGA-II enhanced by controlled elitism.
引用
收藏
页码：1206 / 1210
页数：5
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