An Extension of the CODAS Method Using p,q-Quasirung Orthopair Fuzzy Information: Application in Location Selection for Retail Store

The p , q - quasirung orthopair fuzzy sets represent an innovative advancement in fuzzy set theory, addressing the constraints inherent in q - rung orthopair fuzzy sets. This new extension has gained considerable traction in multi-criteria group decision-making (MCGDM) scenarios. The Combinative Dis...

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Veröffentlicht in:International journal of fuzzy systems Jg. 27; H. 6; S. 1754 - 1770
Hauptverfasser: Alballa, Tmader, Rahim, Muhammad, Aloraini, Najla M., Khalifa, Hamiden Abd El-Wahed
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2025
Springer Nature B.V
Schlagworte:
Artificial Intelligence
Comparative studies
Computational Intelligence
Decision making
Engineering
Flexibility
Fuzzy set theory
Fuzzy sets
Group theory
Management Science
Medical wastes
Methods
Multiple criteria decision making
Multiple criterion
Operations Research
Project evaluation
Sensitivity analysis
Site selection
Location selection for retail store
quasirung orthopair fuzzy sets
CODAS method
Decision making
ISSN:1562-2479, 2199-3211
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Zusammenfassung:The p , q - quasirung orthopair fuzzy sets represent an innovative advancement in fuzzy set theory, addressing the constraints inherent in q - rung orthopair fuzzy sets. This new extension has gained considerable traction in multi-criteria group decision-making (MCGDM) scenarios. The Combinative Distance-based Assessment (CODAS) method is designed to enhance the multi-criteria selection process by maximizing both Euclidean and Taxicab distances relative to negative ideal solutions. In the literature, different extensions are proposed. However, these extensions are unable to address situations where decision makers may employ varying term levels for membership degrees. To bridge this gap, this paper enhances the traditional CODAS method by incorporating p , q - quasirung orthopair fuzzy ( p , q - QOF) numbers to effectively solve multi-criteria group decision-making (MCGDM) problems with incomplete weight information. The proposed CODAS approach enables decision makers to set distinct term levels ( p and q ) for membership and non-membership, enhancing evaluation precision. To illustrate the application of the proposed approach, a numerical example pertaining to retail location selection is presented. The comparative study demonstrates the superiority of the proposed approach over several relevant methods. In addition, a sensitivity analysis of the proposed CODAS method, conducted by varying the criteria weights, reveals a high degree of stability in the results.
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ISSN:1562-2479
2199-3211
DOI:10.1007/s40815-024-01870-5