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

ABSTRACT 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 () operator and the single‐valued neutrosophic prioritised geometric () 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.

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Publication Details

Journal
CAAI Transactions on Intelligence Technology
Published
2025-12-05
DOI
https://doi.org/10.1049/cit2.70058
Primary Topic
Multi-Criteria Decision Making
Type
article
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article

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

Hafiz Muhammad Athar Farid, Ayesha Razzaq, Muhammad Riaz, Sarbast Moslem et al.
CAAI Transactions on Intelligence Technology
Multi-Criteria Decision Making
article

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

Hafiz Muhammad Athar Farid, Ayesha Razzaq, Muhammad Riaz, Sarbast Moslem, Tapan Senapati
article en

Abstract

ABSTRACT 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 () operator and the single‐valued neutrosophic prioritised geometric () 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.

CAAI Transactions on Intelligence TechnologyVol. 11(1)
University College Dublin (IE), University of Huddersfield (GB), Southwest University (CN), University of the Punjab (PK), Trinity College Dublin (IE), Azerbaijan State University of Economics (AZ), Chitkara University (IN), Saveetha University (IN)
Openalex Percentile: Top 56%
Multi-Criteria Decision Making
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