Fuzzy multiobjective 0-1 programming through revised genetic algorithms

We consider multi-objective 0-1 programming problems and propose the fuzzy decision making method based on revised genetic algorithms. In the proposed method, by considering the imprecise nature of human judgements, it is assumed that the decision maker (DM) has a fuzzy goal for each of the objective functions and adopt the minimum-operator for combining the membership functions for fuzzy goals of the DM. Then the formulated problem can be reduced to the usual 0-1 programming problems. We propose the revised genetic algorithm in which the “random 0-1 reverse method” is introduced to deal with the linear constraints whose parameters may be positive or negative. We apply the proposed method to two types of problems: the real-world decision making problem, i.e., the media selection planning problem; and the numerical examples which involves 3 objectives, 30 variables and 5, 10 or 15 constraints, and whose parameters are generated at random