Linguistic Truth-Valued Multi-Attribute Decision Making Approach Based on TOPSIS

In order to solve multi-attribute decision making (MADM) problem with fuzzy linguistic-valued information, a linguistic truth-valued MADM approach based on TOPSIS is proposed in combination with traditional TOPSIS approach. Based on linguistic truth-valued lattice implication algebra, the approach uses linguistic truth values to express fuzzy linguistic-valued information which is both comparable and incomparable. Then we define the normalized distance algorithm of linguistic truth values, and its related properties are discussed. The definitions of linguistic truth-valued positive and negative ideal points are proposed, the distances between every alternative and positive ideal alternative or the distances between every alternative and negative ideal alternative are calculated, obtaining the relative degree of closeness between every alternative and ideal alternatives. Come out the best alternative according to the ranking result of relative degree of closeness. The validity and the feasibility of the proposed decision making approach is illustrated by an example.