No abstract

This paper proposes a new multiobjective fuzzy optimization method. First, the unsatisfying function, which is more useful and effective as the expression of fuzziness for optimization problems than the membership function, is introduced. The multiobjective optimization problem is transformed into a satisficing problem by using aspiration levels, and the fuzzy satisficing problem is formulated. Then, the interactive design method to minimize the maximum unsatisfaction rating by Genetic Algorithm is proposed. The effectiveness of the proposed method is demonstrated by the design example of an active suspension system. The trade-off graph is used in order to seek a satisficing solution, which reflects the designer's preference, more interactively and graphically.

No abstract

No abstract

No abstract