A Single-Valued Neutrosophic TOPSIS Model for Supplier

Selection under Indeterminate Judgements: A Decision-Support

Perspective on Information Fusion

Indu Duhari1,* Naglaa Fathi2

1 Jawaharlal Nehru University, India

2 Department of Computer Science, Benha University, Egypt

Received: July 02, 2025 Accepted: September 15, 2025 ⋆ Corresponding author

ABSTRACT

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.

Keywords: Neutrosophic sets Information fusion Single-valued neutrosophic TOPSIS Multi-criteria decision-making

Supplier selection Indeterminacy

1. INTRODUCTION

Purchasing decisions bind a firm to a supplier for months

or years, so the selection of that supplier is among the most

consequential operational decisions a company makes. A

poor choice propagates downstream as late deliveries, quality

escapes, warranty costs and reputational damage, and it

is expensive to reverse because switching suppliers incurs

qualification, tooling and relationship costs. The difficulty

is that the deciding criteria—price, quality, delivery reliability,

after-sales service, financial stability and environmental

compliance—pull in different directions and are assessed by

a committee whose members are seldom certain.

The stakes are quantitatively large. Across manufacturing sectors,

purchased materials and components typically account

for more than half of the cost of goods sold, so even a small

improvement in supplier quality or reliability flows straight to

the bottom line, while a single unreliable supplier can idle a

production line and trigger contractual penalties far exceeding

the value of the parts themselves. This asymmetry—modest

upside from a good choice, severe downside from a bad one—

is precisely why practitioners are uncomfortable committing

to crisp scores they do not really believe.