A hybrid approach for resilient sourcing and supply chain network design

In the face of increasing global uncertainties and the growing vulnerability of supply chains to disruptions, designing resilient supply chains has emerged as a critical challenge for modern businesses. We aim to present a novel two-phase hybrid approach for designing a supply chain resilient to major disruptions and operational interruptions. The first phase of the proposed approach focuses on evaluating the supplier performance using a unified data envelopment analysis model. Using the obtained scores, the second phase then determines outsourcing and network design decisions using a stochastic robust bi-objective optimization model. The optimization model minimizes the total supply chain cost and maximizes the overall supplier performance. To enhance the supply chain resilience, a number of reactive and proactive risk mitigation strategies are incorporated in the model. These strategies include multiple sourcing, facility fortification, the use of substitutable products, extra production capacities, and holding safety stock inventory. An accelerated Benders decomposition algorithm is developed to solve the proposed model. The application of the proposed model and approach is investigated using data from a real case study. The practical results and their implications are discussed. Our analyses focus on (1) exploring the relationship between supplier performance level and supply chain cost, (2) examining the impact of the unified data envelopment analysis model on sourcing decisions, (3) evaluating the effectiveness of resilience strategies, (4) analyzing the advantages of the proposed solution approach for solving problems of different sizes and (5) assessing the performance of the proposed stochastic programming approach.