A Novel Generalization of Hesitant Fuzzy Model with Application in Sustainable Supply Chain Optimization

Subject Areas : Transactions on Fuzzy Sets and Systems

Wajid Ali ^{1 *} , Tanzeela Shaheen ² , Iftikhar Ul Haq ³ , Mohammad Mehedi Hassan ⁴

1 - Department of Mathematics, Air University Islamabad, Islamabad, Pakistan.
2 - Department of Mathematics, Air University Islamabad, Islamabad, Pakistan.
3 - Department of Mathematics, Air University Islamabad, Islamabad, Pakistan.
4 - Information Systems Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.

Received: 2024-07-26 Accepted : 2024-09-25 Published : 2025-02-13

Keywords: Hesitant fuzzy sets, c, d‐rung orthopair fuzzy sets, Decision making, MADM, Sustainable supply chain.,

Abstract :

The n,m‐rung orthopair fuzzy set theory is a robust model for managing uncertainty, particularly in multi‐attribute  decision‐making. Meanwhile, the hesitant fuzzy model is a well‐established tool in decision‐making processes. Recognizing the  similarities between these models, we propose a new framework called "c,d‐rung orthopair hesitant fuzzy sets," which integrates  both approaches. We examine key operations such as union, intersection, complement, subset, and equality, and introduce  aggregation operators like the c,d‐RHFPA, c,d‐RHFWA, c,d‐RHFPG, and c,d‐RHFWPG operators. Additionally, an algorithm for  multi‐attribute decision‐making is developed, which is applied to determine optimal business strategies for sustainable supply chain management. A comparative analysis with existing methods demonstrates the model's effectiveness, offering insights into  its strengths and limitations. This paper introduces a novel approach to decision‐making, outlining its real‐world application and  future research directions

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