Decision-Making Framework for Supplier Selection Using an Integrated Approach of Dempster-Shafer Theory and Maximum Entropy Principle

The process of supplier selection plays a crucial role in determining the success and competitiveness of organizations in today's dynamic business environment. To make informed decisions, decision-makers often rely on robust and efficient methods that consider multiple criteria simultaneously. In this regard, this paper presents a novel approach that combines the Dempster-Shafer theory and the Maximum Entropy Principle to address the supplier selection problem effectively. Dempster-Shafer theory, rooted in evidence theory, provides a powerful framework for handling uncertainty and incomplete information in decision-making. It allows decision-makers to represent and combine evidence from multiple sources, leading to more reliable and rational decisions. On the other hand, the Maximum Entropy Principle, a principle of statistical inference, is widely used for incorporating prior knowledge into decision-making processes. Our proposed approach harnesses the strengths of both the Dempster-Shafer theory and the Maximum Entropy Principle to enhance the supplier selection process. The decision-making framework is designed to handle the inherent uncertainty, subjectivity, and imprecision associated with the supplier selection problem. The flexibility and robustness of the method are demonstrated by the comparative and sensitivity analysis.