Complex Pentapartitioned Neutrosophic Aggregation Operators with an Application in the Selection of Millets for Cultivation

Porchudar T; Ajay D; Sathinathan T; John Borg S

Authors

Porchudar T Sacred Heart College (Autonomous), Tirupattur-635 601, Affiliated to Thiruvalluvar University, Serkkadu, Vellore, Tamilnadu, India;
Ajay D Sacred Heart College (Autonomous), Tirupattur-635 601, Affiliated to Thiruvalluvar University, Serkkadu, Vellore, Tamilnadu, India;
Sathinathan T Sacred Heart College (Autonomous), Tirupattur-635 601, Affiliated to Thiruvalluvar University, Serkkadu, Vellore, Tamilnadu, India
John Borg S Sacred Heart College (Autonomous), Tirupattur-635 601, Affiliated to Thiruvalluvar University, Serkkadu, Vellore, Tamilnadu, India

Keywords:

: C-PNS, Aggregation Operator, Millets Cultivation, MCDM.

Abstract

The Complex Pentapartitioned Neutrosophic Set (C-PNS) is an advanced generalization of Fuzzy
Sets, designed to model complex uncertainties characterized by periodic, vague and indeterminate information.
In this study, we introduce two novel aggregation operators tailored for C-PNS environments: the Complex
Pentapartitioned Neutrosophic Weighted Arithmetic Average (CPNWAA) and the Complex Pentapartitioned
Neutrosophic Weighted Geometric Average (CPNWGA) operators. We establish their mathematical properties,
including idempotency, boundedness and monotonicity, ensuring their theoretical soundness and applicability
in decision-making scenarios. To demonstrate the utility of the proposed operators, we apply them to a MultiCriteria Decision-Making (MCDM) problem focused on selecting the most suitable millet variety for cultivation
under uncertain conditions. Evaluations were conducted with inputs from three domain experts, considering
multiple cultivation-related criteria. The analysis reveals that Ragi (finger millet) emerges as the most optimal
choice among the alternatives. Furthermore, comparative studies with existing MCDM methods; WSM, WPM,
N-TOPSIS, N-WASPAS and N-MOORA along side statistical validation, confirm the robustness, consistency
and effectiveness of our proposed methodology. This research not only enriches the C-PNS framework with new
tools but also provides a reliable and flexible approach to decision-making in complex agricultural contexts

DOI: 10.5281/zenodo.17041904