Implication Relations, Equivalence Relations and Hierarchical Structure of Attributes in Multiple Criteria Decision Making

摘要: This paper presents an efficient technique for computing implication structures, especially Multiple Attribute Decision Making (MADM) problems. The method based on the generalized modus ponens. Implication means that there is a membership of binary relation good performance level attribute Ai implies other Aj each combination. Obviously, if such implications are found one can get some positive effects: 1 reduction number relevant attributes, 2 computing measuring inner contradictions between attributes decision making problem, 3 obtaining hierarchy attributes. Equivalence classes arise during computation. Basic information given by matrix. needs upper and lower satisfaction levels single criterion. Using so-called threshold, maker, crisp structure equivalence classes. A contradiction leads to degree carefulness, needed in following MADM steps. Some methods (like, instance, Saaty’s hierarchical method) method, presented this paper, helps case, cannot be maker.