An interactive fuzzy satisficing approach using genetic algorithm for multi-objective problems
Takanori KIYOTA, Y. Tsuji, Eiji Kondo · 2002
This paper describes a fuzzy satisficing method for multi-objective optimization problems using a genetic algorithm (GA). A multi-objective design problem with constraints is expressed as a constraint satisfaction problem by introducing an aspiration level for each objective. In order to handle the fuzziness involved in aspiration levels and constraints, the "unsatisfying function" is introduced, and the problem is formulated as a multi-objective minimization problem of unsatisfaction ratings. As the optimization method, a GA is employed. One can seek a satisficing solution by modifying the parameters interactively according to one's preferences.