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

Abstract:

In this paper, we propose δ-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. Copyright © 2008 The Institute of Electronics, Information and Communication Engineers.

Año de publicación:

2008

Keywords:

• δ-similar elimination
• Multiobjective evolutionary algorithms
• Controlled elitism
• Selection

Fuente:

scopus