A multiple attribute group decision making model based on 2-tuple linguistic pythagorean fuzzy dombi aggregation operators for optimal selection of potential global suppliers
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View abstract on PubMed
Summary
This summary is machine-generated.This study introduces new Dombi aggregation operators for 2-Tuple Linguistic Pythagorean Fuzzy Numbers (2TLPFNs) to enhance Multiple-Attribute Group Decision-Making (MAGDM) under uncertainty. A novel model is proposed and validated for complex decision scenarios.
Area Of Science
- Decision Sciences
- Fuzzy Logic and Uncertainty Quantification
- Operations Research
Background
- Multiple-Attribute Group Decision-Making (MAGDM) is crucial for complex choices, often involving uncertain information.
- Pythagorean Fuzzy Sets (PFS) extend Intuitionistic Fuzzy Sets (IFS), offering robust representation of uncertainty.
- 2-Tuple Linguistic Pythagorean Fuzzy Numbers (2TLPFN) integrate linguistic terms with PFS for nuanced decision modeling.
Purpose Of The Study
- To develop novel Dombi aggregation operators for 2-Tuple Linguistic Pythagorean Fuzzy Numbers (2TLPFNs).
- To propose and validate a MAGDM model utilizing these new operators within the 2TLPF environment.
- To enhance the flexibility and applicability of Dombi operations in decision-making.
Main Methods
- Construction of 2-Tuple Linguistic Pythagorean Fuzzy (2TLPF) Dombi Aggregation operators: 2TLPFDWA, 2TLPFDOWA, 2TLPFDWG, and 2TLPFDOWA.
- Analysis of the unique characteristics and properties of the newly developed aggregation operators.
- Development of a MAGDM model leveraging these operators for decision problems in the 2TLPF environment.
Main Results
- Successfully formulated and analyzed four novel 2TLPF Dombi aggregation operators.
- Demonstrated the effectiveness of the proposed MAGDM model through a practical case study.
- Validated the model's implementation, resilience, and applicability in handling uncertain group decisions.
Conclusions
- The developed 2TLPF Dombi aggregation operators provide a flexible and effective tool for MAGDM.
- The proposed MAGDM model offers a robust framework for addressing complex decisions with linguistic uncertainty.
- The research contributes to advancing decision-making methodologies by integrating PFS, linguistic terms, and Dombi operations.
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