Extension of Classical TOPSIS Method Using Q-Rung Orthopair Triangular Fuzzy Number

Meltem Yontar Aksoy, Ayse Nur Karabayır and Zahide Ozden Ceylan Gungor
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Meltem Yontar Aksoy: Department of Industrial Engineering, Istanbul Technical University, Faculty of Management, Istanbul, Turkey
Ayse Nur Karabayır: Department of Industrial Engineering, University of Passau, Passau, Germany
Zahide Ozden Ceylan Gungor: Department of Industrial Engineering, Istanbul Technical University, Faculty of Management, Istanbul, Turkey

Advances in Decision Sciences, 2022, vol. 26, issue 1, 163-187

Abstract: Purpose: As an extension of pythagorean fuzzy sets, the q-rung orthopair fuzzy sets (q-ROFS) is proposed by Yager in 2017. The q-ROFS offers a novel calculation form for the loss function and effectively deals with unclear information of multi-attribute decision-making (MADM) problems. The concept of q-rung orthopair fuzzy number (q-ROFN) is introduced to facilitate the use of q-ROFS in 2018. This study proposes a comprehensive q-rung orthopair triangular fuzzy number (q-ROTFN) which is a special notation of q-ROFN, to cope with supplier selection problems. Design/methodology/approach: A new method is developed in this paper for supplier selection MADM problems in uncertain situations. The proposed technique utilizes experts' knowledge represented by q-ROFN. It considers the selection of the most proper supplier taking into account flexibility, quality, price, supplier profile, and delivery criteria. Based on the advantages of q-ROFN, this article proposes an extended fuzzy TOPSIS method that does not require aggregation technology. Findings: To verify the proposed technique, a case study is conducted to evaluate and rank the alternative suppliers for an automotive company. As a result of the outcomes, it is shown that the proposed method is suitable for MADM problems. Originality/value: The main contributions of this paper are as follows: (i) Traditional TOPSIS method has been extended using the q-ROTFN to solve multi-attribute decision problems, (ii) It is shown that aggregation techniques are not needed for q-ROTFN based TOPSIS method, (iii) A novel expert weight calculation technique is proposed.

Keywords: Q-Rung orthopair fuzzy number; TOPSIS; supplier selection; multiple attribute decision-making (search for similar items in EconPapers)
JEL-codes: D7 D81 (search for similar items in EconPapers)
Date: 2022
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