Bipolar Neutrosophic Aczel-Alsina Aggregation for Effective Group Decision-Making

Abstract

This paper presents a series of innovative Bipolar Neutrosophic Aggregation Operators to address the complexity and uncertainty in Multiple Criteria Decision-Making scenarios. The newly proposed operators BNAAWA, BNAAOWA, BNAAHWA, BNAAWG, BNAAOWG, and BNAAHWG are designed to enhance aggregation under bipolar neutrosophic conditions, capturing a more nuanced view of decision-makers' preferences. We develop the MCDM method with the BNN. The effectiveness of these operators is demonstrated through a detailed case study, where they are applied to a complex decision-making scenario involving conflicting and uncertain criteria. Comparative and sensitivity analyses are conducted to assess the stability, reliability, and adaptability of each operator, benchmarking them against existing approaches. The results reveal that the proposed operators significantly improve decision-making accuracy by accommodating bipolar information and managing degrees of uncertainty more effectively. In the Results and Discussion section, we explore how each operator performs across varied MCDM contexts, highlighting the flexibility and robustness of the bipolar neutrosophic framework. The paper concludes by discussing the limitations of the proposed operators, offering insights into potential applications, and suggesting directions for future research to further refine bipolar neutrosophic-based MCDM approaches. This work contributes a comprehensive, operator-based method for enhanced decision-making under complex and uncertain conditions.