A model of consensus in group decision making under linguistic assessments
Fuzzy Sets and Systems
Combining numerical and linguistic information in group decision making
Information Sciences: an International Journal
Extensions of the TOPSIS for group decision-making under fuzzy environment
Fuzzy Sets and Systems
Linguistic decision analysis: steps for solving decision problems under linguistic information
Fuzzy Sets and Systems - Special issue on soft decision analysis
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
A new approach for fuzzy risk analysis based on similarity measures of generalized fuzzy numbers
Expert Systems with Applications: An International Journal
Similarity relations and fuzzy orderings
Information Sciences: an International Journal
A note on two methods for estimating missing pairwise preference values
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A web based consensus support system for group decision making problems and incomplete preferences
Information Sciences: an International Journal
Group decision making problems in a linguistic and dynamic context
Expert Systems with Applications: An International Journal
A mobile decision support system for dynamic group decision-making problems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Manufacturing delivery performance for supply chain management
Mathematical and Computer Modelling: An International Journal
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It is proposed to use fuzzy similarity in fuzzy decision-making approach to deal with the supplier selection problem in supply chain system. According to the concept of fuzzy TOPSIS earlier methods use closeness coefficient which is defined to determine the ranking order of all suppliers by calculating the distances to both fuzzy positive-ideal solution (FPIS) and fuzzy negative-ideal solution (FNIS) simultaneously. In this paper we propose a new method by doing the ranking using similarity. New proposed method can do ranking with less computations than original fuzzy TOPSIS. We also propose three different cases for selection of FPIS and FNIS and compare closeness coefficient criteria and fuzzy similarity criteria. Numerical example is used to demonstrate the process. Results show that the proposed model is well suited formultiple criteria decision-making for supplier selection. In this paper we also show that the evaluation of the supplier using traditional fuzzy TOPSIS depends highly on FPIS and FNIS, and one needs to select suitable fuzzy ideal solution to get reasonable evaluation.