A new multicriteria decision making method based on the topsis method and similarity measures between intuitionistic fuzzy sets
Shyi‐Ming Chen, Shou-Hsiung Cheng, Tzu-Chun Lan · 2016
This paper proposes a novel multicriteria decision making (MCDM) method using the TOPSIS method and similarity measures between intuitionistic fuzzy values. First, it calculates the degree of indeterminacy (DOI) of each evaluating intuitionistic fuzzy value (IFV) given by the decision maker. Then, it calculates the DOI of the relative positive ideal value (RPIV) and the relative negative ideal value (RNIV) for each criterion, respectively. Then, it calculates the positive similarity degrees and the negative similarity degrees. Finally, it calculates the weighted positive score and the weighted negative score of each alternative, respectively, to get the relative degree of closeness of each alternative. The advantage of the proposed MCDM method is that it can overcome the drawbacks of the existing MCDM methods for MCDM in intuitionistic fuzzy environments.