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

Aksoy M. Y., Karabayir A. N., Göngör Z. Ö. C.

Advances in Decision Sciences, vol.26, no.1, 2022 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 26 Issue: 1
  • Publication Date: 2022
  • Doi Number: 10.47654/v26y2022i1p163-187
  • Journal Name: Advances in Decision Sciences
  • Journal Indexes: Scopus, ABI/INFORM, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Computer & Applied Sciences, zbMATH, Directory of Open Access Journals
  • Keywords: Multiple attribute decision-making, Q-Rung orthopair fuzzy number, Supplier selection, TOPSIS
  • Istanbul Technical University Affiliated: Yes


© 2022 Hindawi Limited. All rights reserved.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.