Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Decomposed Fuzzy Sets and Their Usage in Multi-Attribute Decision Making: A Novel Decomposed Fuzzy TOPSIS Method

Version 1 : Received: 19 June 2023 / Approved: 20 June 2023 / Online: 20 June 2023 (07:42:16 CEST)

A peer-reviewed article of this Preprint also exists.

Kahraman, C.; Cebi, S.; Oztaysi, B.; Cevik Onar, S. Intuitionistic Fuzzy Sets with Ordered Pairs and Their Usage in Multi-Attribute Decision Making: A Novel Intuitionistic Fuzzy TOPSIS Method with Ordered Pairs. Mathematics 2023, 11, 3867. Kahraman, C.; Cebi, S.; Oztaysi, B.; Cevik Onar, S. Intuitionistic Fuzzy Sets with Ordered Pairs and Their Usage in Multi-Attribute Decision Making: A Novel Intuitionistic Fuzzy TOPSIS Method with Ordered Pairs. Mathematics 2023, 11, 3867.

Abstract

Decomposed fuzzy sets are the resent extension of intuitionistic fuzzy sets by incorporating functional and dysfunctional points of views to the definition of membership functions. This paper extends the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) method to the Decomposed Fuzzy TOPSIS (DF TOPSIS) method and applies it to a multi-criteria risk-based supplier selection problem under fuzziness. DF TOPSIS involves finding a positive ideal solution and a negative ideal solution and measuring the distance of each alternative to these solutions. The final ranking is obtained based on the proportion of distances to the positive and negative ideal solutions. The developed DF TOPSIS method incorporates the accuracy and consistency of expert judgments, enhancing the decision-making process. A sensitivity analysis is also presented in order to show the robustness of the obtained rankings by DF TOPSIS.

Keywords

Intuitionistic fuzzy sets; Decomposed fuzzy sets; TOPSIS; Risk analysis; Supplier selection problem

Subject

Engineering, Industrial and Manufacturing Engineering

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