Comparative study between GRA and MEREC technique on an agricultural-based MCGDM problem in pentagonal neutrosophic...

Area of Science:

• Decision Sciences
• Operations Research
• Artificial Intelligence

Background:

• Existing Multi-criteria Group Decision-Making (MCGDM) methods struggle with uncertainty and robustness.
• Pentagonal Neutrosophic Numbers (PNNs) offer a framework to handle complex uncertainties.
• Integrating Grey Relational Analysis and MEREC techniques can enhance MCGDM performance.

Purpose of the Study:

• To develop an improved MCGDM strategy within a pentagonal neutrosophic environment.
• To enhance the ability of MCGDM techniques to capture and manage uncertainties robustly.
• To provide consistent and rigorous decision-making results.

Main Methods:

• Development of an improved MCGDM strategy combining Grey Relational Analysis and MEREC.
• Introduction of Hamming distance for Pentagonal Neutrosophic Numbers (PNNs).
• Application of weighted arithmetic and geometric averaging operators in the PNN environment.
• Illustration using an agriculture-based numerical problem.

Main Results:

• The proposed MCGDM strategy demonstrates robustness and consistency.
• Evaluation of an agricultural problem identified 'plantation crop' as the best alternative under specific conditions.
• Sensitivity analysis confirmed the stability of the best-ranked alternative across different aggregation operators.

Conclusions:

• The enhanced MCGDM methodology effectively handles uncertainties in decision-making.
• The integration of PNNs, Grey Relational Analysis, and MEREC provides a robust decision-making framework.
• The study validates the consistency and reliability of the proposed computational technique.