Akademik Veri Yönetim Sistemi
OPERATIONAL RESEARCH, cilt.25, sa.2, 2025 (SCI-Expanded, Scopus)
The medical supply chain (MSC) plays a crucial role in ensuring that drugs, vaccines, gloves, and other medical products are delivered to the right place at the right times and in the required quantity. For this reason, the viability of MSC is vital in case of an external risk such as the coronavirus (COVID-19) pandemic. The COVID-19 pandemic is a type of ripple effect that has devastating effect on supply chain performance. With that in mind, to the best of our knowledge, this study explores a bi-objective MSC design problem under uncertainty caused by the ripple effect for the first time. Accordingly, a generic bi-objective robust optimization model is fundamentally developed to represent the addressed problem mathematically by considering the uncertainty sourcing from pandemic. To obtain applicable results, a real case study is considered for MSC design in Istanbul/Turkey as a practical contribution by validating the optimization model. Furthermore, a set of scenarios are generated by placing an emphasis on the decrease in capacity utilization rates and the increase in product demand due to the pandemic. A computational study is conducted through scenarios and risk mitigation strategies to reveal managerial insights by combining the strategic and operational level decisions regarding the MSC network. The improved augmented & varepsilon;-constrained (AUGMECON2) method is employed to obtain diversified Pareto-optimal solutions for all problems. Several comparison metrics are employed to further analyze the solutions from different perspectives. According to the computational results attained by extensive experiments, a unified strategy is proposed to achieve MSC resiliency. Besides, solving large sized problem instances through the proposed methodology is highlighted as the main limitation of this study.