Extension of Classical TOPSIS Method Using Q-Rung Orthopair Triangular Fuzzy Number
Keywords:Q-Rung orthopair fuzzy sets, TOPSIS, supplier selection, multiple attribute group decision-making
Purpose- As an extension of pythagorean fuzzy sets, the q‐rung orthopair fuzzy sets (q‐ROFSs) can effectively deal with unclear information in Multi Attribute Decision Making (MADM) problems. This manuscript proposes a comprehensive model to cope with supplier selection multi-attribute group decision-making (MAGDM) problem.
Design/methodology/approach- The paper presents a new method for supplier selection multi-attribute group decision making (MAGDM) problems in uncertain situations. The technique utilizes experts' knowledge represented by q-rung orthopair fuzzy sets. It considers the suitability of a supplier (i.e., flexibility, quality, price, supplier profile, delivery) using constructed new fuzzy TOPSIS approach. With the advantages of the calculation model not needing aggregation operators and the superiority of q-ROFNs, this manuscript attempts to extend the traditional TOPSIS method using q-rung orthopair triangular fuzzy sets. The extended classical TOPSIS method using q-rung orthopair triangular fuzzy number (q-ROTFN) is constructed in 13 steps.
Findings- To verify the proposed technique, this study used it for assessing and ranking suppliers in the automotive industry. The results exhibited the success and superiority of the proposed method.
Originality/value-The main contributions of this paper are as follows: (i) To solve multi-attribute decision problems, this study extends the traditional TOPSIS method to the q-rung orthopair fuzzy, (ii) This manuscript presents q-rung orthopair triangular fuzzy TOPSIS method not needing aggregation techniques, (iii) This paper proposes a novel expert weight calculation technique. (iv) The proposed model is applied for assessing and ranking suppliers in the automotive industry.
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