A Robust Biobjective Model for Designing Resilient Supply Chain Networks for Hospitals With Integrated Financial and Physical Flows DOI Creative Commons
Dan Wu,

Amruth Ramesh Thelkar

Discrete Dynamics in Nature and Society, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

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

Language: Английский

A Robust Biobjective Model for Designing Resilient Supply Chain Networks for Hospitals With Integrated Financial and Physical Flows DOI Creative Commons
Dan Wu,

Amruth Ramesh Thelkar

Discrete Dynamics in Nature and Society, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

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

Language: Английский

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