A new approach for multiobjective decision making based on fuzzy distance minimization

The aim of this paper is to design flexible decision making models in the distance metric optimization framework for problems including parameters which are represented by fuzzy numbers. criteria decision making methodologies based on distance functions involve the minimization of some form of distance from a desired point (ideal or specified by a decision marker). If it is assumed that the parameters of problem are fuzzy numbers, then it is natural to expect that this point also is so. Thus, in this paper it is supposed that the desired point is a vector of fuzzy numbers obtained from the imprecise information provided by the decision marker or, alternatively, composed by the individual optimum of each objective under consideration. The methodological proposal is an extension of the distance-based models and relies in the first instance, on the constructing of a fuzzy minimum distance obtained by solving linear programming problems. Secondly, it is shown that this fuzzy minimum distance possesses suitable features with respect to the quality and handling of information such that it can be incorporated in distance-based ordinary models which are necessary in order to determine an optimum decision. To illustrate the suitability of the method, a numerical example has been included.