Integrated Methodology for Multi – Person – Multi Objective Decision Making in Intuitionistic Fuzzy Environment

In this paper, multi – person – multi objective decision making in intuitionistic fuzzy environment is discussed using integrated methodology. And this new approach is also explained with an application. Many decision making problems involve multiple decision makers and conflicting objectives. This paper refers to this kind of problems as group decision making for multi-objective problems (GDM-MOP). The task of GDM-MOP is to select final solution(s) from a set of non-dominated solutions according to the decision makers′ preferences. However, it is common that the preference could be imprecise. We study the GDM-MOP where preferences are expressed by fuzzy reference points, called as fuzzy GDMMOP (FGDM-MOP). This paper provides a decision support model to simultaneously consider two measures for FGDM-MOP: consensus measure and robustness measure. The former is used to reflect the acceptable degree of a solution by the decision making group, while the latter indicates a solution′s ability to cope with any change on preferences. A multi-objective evolutionary approach is presented to solve the problem. Finally, a modified benchmark function is studied to illustrate the proposed approach.