aspg-39-4467-1792222459 20261017073419 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Neutrosophic and Information Fusion NIF 2836-7863 2026 6 1 Indu Duhari Jawaharlal Nehru University, India Naglaa Fathi Department of Computer Science, Benha University, Egypt Supplier selection is a recurrent multi-criteria decision-making (MCDM) problem in which expert judgements are rarely crisp: procurement managers routinely hesitate, disagree, and abstain. Classical fuzzy models capture membership and (at most) non-membership, but they cannot separately encode the indeterminacy that pervades real committee evaluations. This paper develops a supplier-selection model built on single-valued neutrosophic sets (SVNSs), where every judgement is represented by an independent triple of truth, indeterminacy and falsity degrees. Group opinions are aggregated by a single-valued neutrosophic weighted averaging operator, providing a transparent information-fusion step, after which an extended TOPSIS procedure ranks the alternatives by their relative closeness to neutrosophic ideal solutions. A worked case with five suppliers and six criteria illustrates the pipeline end to end, and a sensitivity study over the score function and criteria weights confirms that the top-ranked supplier is stable across 200 weight perturbations. Benchmarked against fuzzy-TOPSIS and intuitionistic-fuzzy TOPSIS baselines, the neutrosophic model separates genuinely ambiguous suppliers from clearly dominated ones more reliably, preserving a wider spread of closeness coefficients in the contested middle of the ranking. 2026 34 39 4467 https://creativecommons.org/licenses/by/4.0/ 10.54216/NIF.060105 https://americaspg.com/journal/39/article/4467 https://americaspg.com/storage/articles/manuscripts/01KYGKDAF0AKK2V143B44FCGKV.pdf