A bi-objective robust optimization model to bolster a resilient medical supply chain in case of the ripple effect

Gökhan Özçelik (), Fatma Betül Yeni (), Beren Gürsoy Yılmaz () and Ömer Faruk Yılmaz ()
Additional contact information
Gökhan Özçelik: Karadeniz Technical University
Fatma Betül Yeni: Karadeniz Technical University
Beren Gürsoy Yılmaz: Karadeniz Technical University
Ömer Faruk Yılmaz: Karadeniz Technical University

Operational Research, 2025, vol. 25, issue 2, No 27, 42 pages

Abstract: Abstract 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 ϵ-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.

Keywords: Medical supply chain; Ripple effect; COVID-19 pandemic; Supply chain resiliency; Bi-objective optimization model (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s12351-025-00928-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:operea:v:25:y:2025:i:2:d:10.1007_s12351-025-00928-y

Ordering information: This journal article can be ordered from
https://www.springer ... search/journal/12351

DOI: 10.1007/s12351-025-00928-y

Access Statistics for this article

Operational Research is currently edited by Nikolaos F. Matsatsinis, John Psarras and Constantin Zopounidis

More articles in Operational Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().