Supplier management is a critical and multifaceted decision-making process in the supply chain, and it becomes even more challenging in uncertain environments. The increasing globalization and disruptions in supply chains have highlighted the need for resilience across all supply chain components. The recognition that maintaining supply chain continuity during disruptive events is crucial has shifted the focus of companies toward prioritizing the selection of resilient suppliers. To address these challenges, this study proposes a multi-stage stochastic resilient supplier selection and order allocation framework that considers operational and disruption risks. In the first stage, a supplier resilience score for each supplier is computed to determine the resilience index for the supplier portfolio based on key resilience criteria. The second stage involves formulating a multi-product, multi-objective stochastic supplier portfolio model involving several practical constraints expressed as chance constraints. In the final stage, the proposed stochastic resilient supplier portfolio model is solved by reformulating it into its deterministic equivalent. The methodology presented is beneficial as it considers both operational and disruption risks. The proposed methodology is illustrated through a numerical case study from the pharmaceutical industry, and sensitivity analyses are performed to assess the robustness of the model and the solution approach. This study presents a comprehensive framework for enhancing supplier selection in supply chain operations by integrating resilience and mitigating risks within the supplier portfolio model.
Sahu et al. (Tue,) studied this question.