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Fermatean fuzzy Linguistic term set based on linguistic scale function with Dombi aggregation operator and their
Omar Barukab1, Asghar Khan2, Sher Afzal Khan3
1Faculty of Computing and Information Technology, King Abdulaziz University, P.O. Box 411, 21911, Rabigh, Jeddah, Saudi Arabia.
Heliyon
|September 12, 2024
Summary
Selecting industrial locations is complex. This study introduces a new Fermatean Fuzzy Linguistic (FFL) approach using Dombi aggregation operators to handle uncertain information, improving multi-criteria decision-making for strategic site selection.
Area of Science:
- Operations Research
- Decision Science
- Fuzzy Set Theory
Background:
- Industrial location selection is a complex multi-criteria decision-making (MCDM) problem.
- Decision-makers often face ambiguous information due to complex environments or limited knowledge.
- Existing methods may struggle with the inherent uncertainty and linguistic vagueness in location selection criteria.
Purpose of the Study:
- To propose a comprehensive framework for strategic industrial location selection.
- To introduce a novel Fermatean Fuzzy Linguistic (FFL) term set for representing uncertain evaluation information.
- To develop a new multi-criteria group decision-making technique based on FFL Dombi aggregation operators.
Main Methods:
- Development of a new Fermatean Fuzzy Linguistic (FFL) term set.
- Establishment of operational principles and aggregation operators (FFLDWA, FFLDWG) for FFL information.
- Construction of a multi-criteria group decision-making technique utilizing the proposed FFL Dombi operators.
- Validation through a numerical example comparing the technique with existing methods.
Main Results:
- The proposed FFL set effectively represents uncertain and linguistic evaluation information.
- The developed FFL Dombi aggregation operators provide robust methods for aggregating fuzzy linguistic data.
- The new decision-making technique demonstrates flexibility and effectiveness in strategic industrial location selection.
- Numerical example confirms the superiority and adaptability of the proposed approach.
Conclusions:
- The Fermatean Fuzzy Linguistic approach offers a powerful tool for handling ambiguity in industrial location selection.
- The integration of Dombi aggregation operators enhances the capability of MCDM methods in complex decision environments.
- The proposed framework provides a reliable and flexible method for identifying optimal industrial sites based on prioritized criteria.
Keywords:
Industrial site selectionLinguistic Fermatean fuzzy Dombi aggregation operators (LFFDAO)Linguistic Fermatean fuzzy set (LFFS)Multi-criteria group decision-making (MCGDM)More Related Videos
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