Fuzzy multi-objective and multi-stage optimization-an application of fuzzy theory to artificial life
H. Kawamura · 2002
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.>