Fuzzy multiobjective integer programs through genetic algorithms using double string representation and information about solutions of continuous relaxation problems

We formulate fuzzy multiobjective integer programming problems considering the vagueness or ambiguity of the decision maker as a human being and introduce an interactive fuzzy satisficing method into them. As a result, the problem to be solved turns out to be an ordinary integer programming problem. For integer programming problems, Sakawa et al. (1997) proposed an approximate solution method based on genetic algorithms using double string representation, but it calls for more improvement on accuracy and processing time. Thus, we attempt to make use of information about solutions of continuous relaxation problems in the genetic algorithm proposed by Sakawa et al., since it is expected to be useful to search the (approximate) optimal solution of the integer programming problem.