RANKING MULTICRITERIA FUZZY ALTERNATIVES IN THE DECISION-MAKERS PREFERENCE SUBSPACE

This paper offers a new procedure for ranking multicriteria fuzzy alte rnatives when the decision-maker subscribes to the notion of 'the larg er, the better'. For each alternative a joint membership function capt ures possible interactions among ratings for each criterion. The ranki ng procedure first orthogonally projects the joint membership function s from the multicriteria decision space to the one-dimensional prefere nce subspace, and then the fuzzy projections are ranked in that subspa ce. A method for generating joint membership functions is introduced, and a numerical example is presented.