Optimising Wave Energy Plant Location Through Neutrosophic Multi-Criteria Group Decision-Making


Farid H. M. A., Razzaq A., Riaz M., Senapati T., MOSLEM S.

CAAI Transactions on Intelligence Technology, 2025 (SCI-Expanded, Scopus) identifier

  • Nəşrin Növü: Article / Article
  • Nəşr tarixi: 2025
  • Doi nömrəsi: 10.1049/cit2.70058
  • jurnalın adı: CAAI Transactions on Intelligence Technology
  • Jurnalın baxıldığı indekslər: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Açar sözlər: aggregation operators, decision making, fuzzy set, priority degrees, sustainable energy
  • Adres: Bəli

Qısa məlumat

The global shift towards sustainable energy has intensified research into renewable sources, particularly wave energy. Pakistan, with its long coastline, holds significant potential for wave energy development. However, identifying optimal locations for wave energy plants involves evaluating complex, multi-faceted criteria. This study employs a multi-criteria group decision-making (MCGDM) approach using single-valued neutrosophic numbers (SVNNs) to address both qualitative and quantitative uncertainties inherent in real-world scenarios. To enhance decision quality, we introduce two novel operators: the single-valued neutrosophic prioritised averaging ((Formula presented.)) operator and the single-valued neutrosophic prioritised geometric ((Formula presented.)) operator, both incorporating priority degrees. These tools allow decision-makers to express preferences better and handle ambiguous data. The proposed model is validated through comparative analysis with prior studies and demonstrates improved robustness in site selection. Furthermore, we analyse how variations in priority degrees influence decision outcomes, enabling a more dynamic and tailored decision-making process. Our method contributes a more holistic and adaptive framework for selecting locations for wave energy projects, ultimately supporting informed investments in renewable energy infrastructure and improving energy access in underserved coastal regions.