A Fuzzy Set and Application of Fuzzy Multi Criteria Decision Making on Vendor Selection

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Y. Robert Meetei, M. Kuber Singh, N. Roshni Devi, T. Vengatesh

Abstract

Vendor selection plays a pivotal role in supply chain management, influencing the efficiency and effectiveness of operations. Traditional vendor selection methods often rely on crisp decision-making frameworks, which may oversimplify complex decision scenarios and neglect uncertainties inherent in real-world situations. This paper explores the application of fuzzy set theory as a novel approach to vendor selection, aiming to enhance decision-making processes in supply chain management.


Drawing from the principles of fuzzy set theory, which allow for the representation of vague or imprecise information, this study proposes a framework that accommodates the inherent uncertainties and ambiguities associated with vendor selection criteria. By employing fuzzy logic and membership functions, the proposed framework enables decision makers to express the degree of membership of vendors to predefined criteria in a more flexible and nuanced manner.


In conclusion, this paper contributes to the ongoing discourse on vendor selection methodologies by introducing a novel approach grounded in fuzzy set theory. By embracing uncertainty and ambiguity, the proposed framework offers a more realistic and adaptable decision-making tool for supply chain practitioners, paving the way for further advancements in the field. A numerical example has been presented to support the proposed model.

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