The Comparison of Two Kinds of Reproduction in Multiobjective Optimization

Author

Yao, Xue-fei ; Liu, Hai-Lin

Author_Institution

Fac. of Appl. Math., Guangdong Univ. of Technol., Guangzhou, China

fYear

2010

fDate

11-14 Dec. 2010

Firstpage

95

Lastpage

99

Abstract

Most of constraint handling papers have focused on the selection of individuals by trade-off the feasible and infeasible regions. This paper studies the effect of two kinds of reproduction in constraint multiobjective optimization. It compares a probabilistic model-based multiobjective evolutionary algorithm to a genetic algorithm. They all use a min-max selection strategy as the main frame structure. The comparison with 19 constraint multiobjective optimization testing instances is given in this paper. The comparison of the instances can show us which reproduction should be used to get a better result when facing different cases.

Keywords

constraint theory; genetic algorithms; minimax techniques; probability; constraint handling; constraint multiobjective optimization; genetic algorithm; min-max selection; probabilistic model-based multiobjective evolutionary algorithm; reproduction strategy; constraint; estimation of distribution algorithm; multiobjective optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security (CIS), 2010 International Conference on

Conference_Location

Nanning

Print_ISBN

978-1-4244-9114-8

Electronic_ISBN

978-0-7695-4297-3

Type

conf

DOI

10.1109/CIS.2010.28

Filename

5696240