The Extended TOPSIS Method for Multi-criteria Decision Making Based on Hesitant Heterogeneous Information

Abstract

In the real world there often exist some decision situations with high degree of uncertainty where the decision makers hesitate among several values to provide their assessments. In such cases, the decision makers usually employ the hesitant fuzzy sets (HFSs) to express their assessments in the quantitative settings and the hesitant fuzzy linguistic term sets (HFLTSs) in the qualitative ones. This paper analyzes a hesitant heterogeneous multi-criteria decision making problem involved both HFSs and HFLTSs. To handle this sort of decision problems, an extended TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is proposed. In the proposed method the separations to the ideal solution and negative ideal solution under each criterion are calculated by using different distance measures, respectively. Then the separations under each criterion are normalized in order to ensure the compatibility of all criteria. Afterwards, the weight separations are derived, and the optimal alternative which is closest to the ideal solution and remotest from negative ideal solution is also identified. At length, an example is used to illustrate the proposed approach. KeywordsHesitant fuzzy sets; hesitant fuzzy linguistic term sets; multi-criteria decision making; TOPSIS