A Robust Biobjective Model for Designing Resilient Supply Chain Networks for Hospitals With Integrated Financial and Physical Flows

In today’s volatile environment, supply chain networks, particularly those in hospitals, are increasingly vulnerable to disruptions, emphasizing the need for integrating resilience strategies into their design. However, the implementation of these strategies introduces financial challenges that must be carefully managed. This study addresses gaps in the existing literature by developing a biobjective optimization model that integrates both financial and physical flows to design resilient supply chain networks under demand uncertainty. The proposed three-level network includes primary and backup suppliers, a factory, and distribution centers. Financial resources such as existing capital, bank loans, and trade credit are considered to improve working capital and ensure operational stability. Trade credit terms and repayment schedules are explicitly modeled across all levels of the supply chain. A proactive fuzzy goal programming approach is employed, and the model is solved using the CPLEX solver. Computational experiments using synthetic data are conducted to evaluate the model’s performance. To illustrate the practical application of the model, a case study based on the hospital equipment supply chain at Nantong First People’s Hospital is used. The results show that the selection of backup suppliers is influenced by financial feasibility, and trade credit plays a crucial role in supporting resilience across multiple levels. This study emphasizes the importance of incorporating financial considerations into the design of resilient hospital supply chains and offers valuable insights for policymakers and practitioners seeking to balance resilience with financial performance.