Fuzzy multi-objective and multi-stage optimization-an application of fuzzy theory to artificial life

Author

Kawamura, Hiroshi

Author_Institution

Dept. of Archit. & Civil Eng., Kobe Univ., Japan

Volume

2

fYear

1995

fDate

20-24 Mar 1995

Firstpage

701

Abstract

This paper presents two new methods of multiobjective optimization. One is an application of simplified genetic algorithm in which membership functions are employed as usual objective functions, and maximizing decision is performed for optimization. The other is a method of membership control in growth processes in which selection is performed also on the way to the final growth step. In such a case of the optimization in regard to the growth of trees, the latter method is proved to be more effective than the former one

Keywords

artificial intelligence; cellular automata; fuzzy set theory; genetic algorithms; trees (mathematics); artificial life; cellular automata; fuzzy multiobjective optimization; fuzzy theory; genetic algorithm; growth processes; membership functions; multi-stage optimization; trees; Automata; Biological cells; Civil engineering; Discrete event simulation; Fuzzy set theory; Fuzzy systems; Genetic algorithms; Optimization methods; Process control; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int

Conference_Location

Yokohama

Print_ISBN

0-7803-2461-7

Type

conf

DOI

10.1109/FUZZY.1995.409760

Filename

409760