Geodesic
A Multi-Attribute Decision Making Context for Supply Chain Management Using Possibility Single-Valued Neutrosophic Soft Settings
Yugoslav journal of operations research, Tome 34 (2024) no. 4, p. 825 .

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Argued decisions, risk estimation, empirical study, forecasts, apprehension supervision, and productive exposition depend on the degree of possibility. It enables us to assess the degree to which specific results are acceptable and to make more informed decisions by drawing on the information at our disposal and logic. Although some scholars have previously examined hybrid structures resembling fuzzy soft sets with possibility degree settings serving as fuzzy membership grades, the current study introduces an innovative structure that permits more adaptable and comprehensive settings: single-valued neutrosophic grades, to serve as possibility degrees. Thus, this study aims to introduce a new mathematical structure, i.e., possibility single-valued neutrosophic soft set (psvNSOS), which combines three important theories (i.e., possibility theory, single-valued neutrosophic theory, and soft set theory). The basic notions, and set-theoretic operations, i.e., union and intersection, of psv-NSOS are investigated and manipulated with matrix representations. Considering evaluating suppliers for a real estate construction project as a multi-attribute decision-making issue, an algorithm that utilizes the matrix manipulations of proposed set-theoretic operations is presented. The suggested algorithm’s robustness is confirmed by comparison to evaluate its dependability and adaptability for modeling uncertainties related to the supplier selection problem.
Classification : 03B52 90B50
Keywords: Possibility degree, single-valued neutrosophic set, soft set, decision making, supply chain management 
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Muhammad Saeed; Muhammed Basit Ali; Atiqe Ur Rahman; Muhammad Yasir Hayat Malik. A Multi-Attribute Decision Making Context for Supply Chain Management Using Possibility Single-Valued Neutrosophic Soft Settings. Yugoslav journal of operations research, Tome 34 (2024) no. 4, p. 825 . http://geodesic.mathdoc.fr/item/YJOR_2024_34_4_a11/