A Possibility Distribution Based Multi-Criteria Decision Algorithm for Resilient Supplier Selection Problems
Dizuo Jiang, Md Mahmudul Hassan, Tasnim Ibn Faiz, Md. Noor-E-Alam

TL;DR
This paper introduces a novel multi-criteria decision-making algorithm that integrates numerical and linguistic evaluations using neutrosophic and fuzzy sets, aimed at resilient supplier selection under uncertainty and conflicting criteria.
Contribution
It develops a comprehensive framework combining SVNS and IVFS for group decision making, extending existing tools to handle both evaluation types for resilient supplier ranking.
Findings
Effective integration of numerical and linguistic criteria.
Successful application of the method in a case study.
Enhanced decision support for resilient supplier selection.
Abstract
Thus far, limited research has been performed on resilient supplier selection - a problem that requires simultaneous consideration of a set of numerical and linguistic evaluation criteria, which are substantially different from traditional supplier selection problem. Essentially, resilient supplier selection entails key sourcing decision for an organization to gain competitive advantage. In the presence of multiple conflicting evaluation criteria, contradicting decision makers, and imprecise decision relevant information (DRI), this problem becomes even more difficult to solve with the classical optimization approaches. However, prior research focusing on MCDA based supplier selection problem has been lacking in the ability to provide a seamless integration of numerical and linguistic evaluation criteria along with the consideration of multiple decision makers. To address these…
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Taxonomy
TopicsMulti-Criteria Decision Making · Supply Chain Resilience and Risk Management · Sustainable Supply Chain Management
