A multi-attribute fuzzy decision making with TOPSIS method based on vague set theory

Abstract

TOPSIS method is an important tool to solve the multiple attribute decision making (MADM) problems. In allusion to the MADM problems that the attribute weights are completely unknown and the attribute values are the vague value. This paper presents a new approach combining TOPSIS with the scoring function to solve above problems. Initially, weights of the attribute are calculated objectively by the method of vague entropy weight coefficient. Secondly, the criteria for scoring function of positive ideal solution and negative ideal solution are established on the basis of advantage of characteristics of the scoring function in the vague set. Then a new kind of relative closeness degree by combining the Euclidean distance with the scoring function is calculated, the alternatives are ranked according to their relative closeness degree. At the end, the testing result of above approach is more efficient and has advantages, which is illustrated with a living example.