Title :
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
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;
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
DOI :
10.1109/FUZZY.1995.409760
