Multiple criteria decision making with generalized data envelopment analysis and an aspiration level method

In this paper, we suggest an aspiration level approach using generalized data envelopment analysis (GDEA) and genetic algorithms in multiple criteria decision making such as engineering design problems. It will be shown that several Pareto optimal solutions close to an aspiration level of decision maker can be listed up as candidates of a final decision making solution by the proposed method. Through the robust design, it will be proved also that the aspiration level method using GDEA is useful for supporting a decision making of complex system.