Automatic construction of fuzzy controllers for evolutionary multiobjective optimization algorithms

Author

Lee, Michael A. ; Esbensen, Henrik

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA

Volume

2

fYear

1996

fDate

8-11 Sep 1996

Firstpage

1518

Abstract

We present techniques for designing fuzzy systems for controlling the behavior of multiobjective evolutionary algorithms. The aim of this work is to develop methods for improving the performance and understanding the behavior of multiobjective evolutionary algorithms. Because the output of a multiobjective optimization algorithm is a set rather than a single point, we present a search performance metric based on a set quality measure. According to this set quality measure, we demonstrate our techniques by developing fuzzy control strategies for a genetic algorithm based IC placement application

Keywords

fuzzy control; fuzzy systems; genetic algorithms; integrated circuit layout; search problems; IC placement application; evolutionary multiobjective optimization algorithms; fuzzy controllers; fuzzy systems; genetic algorithm; search performance metric; set quality measure; Automatic control; Control systems; Costs; Fuzzy control; Fuzzy systems; Genetic algorithms; Integrated circuit layout; Performance evaluation; Production; Q measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on

Conference_Location

New Orleans, LA

Print_ISBN

0-7803-3645-3

Type

conf

DOI

10.1109/FUZZY.1996.552400

Filename

552400