Volume 6 • Issue 2 • PP: 17–21 • 2026
A Neutrosophic Information-Fusion Framework for Renewable-Energy Site Selection under Conflicting Sustainability Criteria
Open Access & Copyright
© 2026 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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Siting a solar or wind farm forces planners to reconcile criteria that disagree by nature: irradiation or wind resource, land cost, grid proximity, ecological sensitivity and social acceptance. The evidence for each criterion is heterogeneous and uncertain—remote-sensing estimates, cadastral records, and public-consultation sentiment—and experts often cannot commit to a definite rating. This paper proposes a neutrosophic information-fusion framework that encodes each expert rating as a single-valued neutrosophic number, derives objective criterion weights by neutrosophic entropy, fuses the ratings with a single-valued neutrosophic weighted geometric operator (which, unlike the arithmetic operator, penalises a poor score on any single criterion), and ranks candidate sites by a deneutrosophied score. Applied to six candidate sites and seven criteria, the framework selects a site that balances a strong resource against low ecological conflict, and a full sensitivity analysis over the weight scheme and the risk attitude shows the choice is robust. A comparison against fuzzy-AHP and SVN-TOPSIS indicates the neutrosophic geometric model better exposes sites whose ranking rests on contested, high-indeterminacy criteria.
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References
[1] J. R. San Cristobal, “Multi-criteria decision-making in the selection of a renewable energy project,” Renewable Energy, vol. 36, no. 2, pp. 498–502, 2011.
[2] H. Z. Ibrahim et al., “A GIS-based multi-criteria decision analysis for solar power plant site selection,” Renewable Energy, vol. 145, pp. 333–346, 2020.
[3] T. L. Saaty, The Analytic Hierarchy Process. McGraw- Hill, 1980.
[4] J. Ye, “Multicriteria decision-making method using the correlation coefficient under single-valued neutrosophic environment,” International Journal of General Systems, vol. 42, no. 4, pp. 386–394, 2013.
[5] J. Ye, “A multicriteria decision-making method using aggregation operators for simplified neutrosophic sets,” Journal of Intelligent & Fuzzy Systems, vol. 26, no. 5, pp. 2459–2466, 2014.
[6] R. Sahin, “Multi-criteria neutrosophic decision making method based on score and accuracy functions under neutrosophic environment,” 2014, arXiv preprint.
[7] P. Liu and Y.Wang, “Multiple attribute decision-making method based on single-valued neutrosophic normalized weighted Bonferroni mean,” Neural Computing and Applications, vol. 25, pp. 2001–2010, 2014.
[8] S. Pramanik, S. Dalapati, and T. K. Roy, “Neutrosophic multi-attribute group decision making strategy for logistics center location selection,” in Neutrosophic Operational Research, 2018, pp. 13–32.
[9] C. Kahraman and I. Otay, Eds., Fuzzy Multi-criteria Decision-Making Using Neutrosophic Sets. Springer, 2019.
[10] P. Majumdar and S. K. Samanta, “On similarity and entropy of neutrosophic sets,” Journal of Intelligent & Fuzzy Systems, vol. 26, no. 3, pp. 1245–1252, 2014.
[11] F. Smarandache, Neutrosophy: Neutrosophic Probability, Set, and Logic. American Research Press, 1998.
[12] A. Aziz et al., “Grey wolf based compressive sensing scheme for data gathering in IoT-based wireless sensor networks,” 2020, author’s prior work.
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