To deal with the concepts of vulnerability, ambiguity, and indeterminacy that are typical in complex decision analysis contexts, neutrosophic set-like structures are frequently used. Although neutrosophic sets are particularly good at handling indeterminate circumstances, indeterminacy plays a part in making the decision making process imprecise and ambiguous. This paper develops a more advanced technique to improve the accuracy of decision analysis problems: the Quantified Possibility Neutrosophic Soft Set Decision Support System (Qt PNSSDSS). In order to reduce the element of indeterminacy present in conventional neutrosophic sets, the proposed DSS is based on the Quantified Neutrosophic Set, which employs a quantification process with a soft set that incorporates the degree of possibility. Using n-norm and n-conorm standards, we establish set-theoretical operations such as union, intersection, and complement. We then analyses their properties with quantified possibility neutrosophic soft subset, null set, and universal set. We implemented the AND-product and OR-product operations to further expand its utility in depicting the interaction between two neutrosophic soft sets with defined possibilities. In this study, a Multi Criteria Decision Making (MCDM) problem of sustainable supply chain management is chosen for the implementation of the suggested Qt PNSSDSS. The procedure is implemented gradually using the operator of AND-product based algorithm upon NSS, PNSS, and then Qt PNSS. Additionally, a graphical representation of the reduction and control of the indeterminacy factor is displayed with the goal of making the evaluated findings using Qt PNSSDSS more precise and understandable. Lastly, a sensitivity and comparison analysis of the research being conducted with a review of existing research is established.
Khalid et al. (Tue,) studied this question.