A Risk Analysis-Based Multi-Attribute Decision-Making Framework for Supply Chain Management Using Hypersoft Mappings

Opting for the right supplier is critical for a firm’s prosperity due to the impact of decisions made on uncertainty in symmetrical decision factors like pricing, manufacturing, service efficiency, and client satisfaction. Deciding on an appropriate supplier can be problematic because there are many considerations to consider, and they occasionally contradict each other. The supplier selection problem (SuSP) has been discussed in the literature in various situations while considering different considerations. Under the symmetry of uncertainty, operational risk analysis is nevertheless inadequate. This study is accomplished in two phases. In the first phase, we delve into the notions, basic properties, and theorems associated with hypersoft mapping (HypSM). These basic features are indispensable, as they endow the theoretical base essential for the subsequent phase. In the second phase, we leverage the aggregations of HypSM to develop a robust decision-assisted mechanism. This mechanism, which incorporates the robust algorithm and SuSP analysis, is constructed directly upon the insights and aggregations explored in the first phase, revealing the practical use of HypSM in decision-making. Concerning soft mapping (SOM), HypSM is more adaptable since its approximate function takes into account multiple argument domains to help decision-makers handle convoluted structural challenges involving uncertainty. Additionally, the proposed decision system considers various operational risks, like material quality-based risks, service quality-based risks, supplier’s market profile-based risks, and deep-rooted cooperation-based risks, for the approximation and evaluation of appropriate suppliers. This approach is expected to enhance decision-making by comprehensively evaluating supplier risks.