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Optimizing construction company selection using einstein weighted aggregation operators for q-rung orthopair fuzzy
Rana Muhammad Zulqarnain1, Imran Siddique2, Abid Mahboob3
1School of Mathematical Sciences, Zhejiang Normal University, Jinhua, 321004, Zhejiang, China. ranazulqarnain7777@gmail.com.
Scientific Reports
|April 20, 2023
Summary
This study introduces Einstein weighted aggregation operators for q-rung orthopair fuzzy hypersoft sets to improve construction project decision-making. The new method enhances multi-criteria group decision-making for selecting construction companies, proving more reliable.
Area of Science:
- Decision Sciences
- Fuzzy Set Theory
- Construction Management
Background:
- Construction project decision-making is complex due to conflicting requirements and uncertainty.
- Existing q-rung orthopair fuzzy soft set (q-ROFSS) models struggle with non-mutually exclusive attributes.
- q-rung orthopair fuzzy hypersoft sets (q-ROFHSS) offer a solution using multi-parameter approximation functions.
Purpose of the Study:
- To introduce Einstein weighted aggregation operators (AOs) for q-rung orthopair fuzzy hypersoft sets (q-ROFHSS).
- To develop a multi-criteria group decision-making (MCGDM) method using these new operators.
- To apply the developed MCGDM model for selecting optimal construction companies.
Main Methods:
- Development of Einstein weighted average and geometric operators for q-ROFHSS.
- Formulation of a novel MCGDM approach based on the proposed Einstein AOs.
- Application of the model to a practical construction company selection scenario.
Main Results:
- The proposed Einstein AOs for q-ROFHSS are mathematically defined and their properties discussed.
- The developed MCGDM method effectively handles complex decision-making in construction.
- Statistical analysis confirms the proposed method's enhanced realism and reliability compared to existing approaches.
Conclusions:
- The novel Einstein weighted aggregation operators for q-ROFHSS provide a robust framework for uncertain decision-making.
- The proposed MCGDM model offers a significant advancement for selecting construction companies.
- This research provides valuable tools for optimizing decision processes and project outcomes in the construction industry.
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