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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 \u03f5-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.  <\/jats:p>","DOI":"10.1007\/s12351-025-00928-y","type":"journal-article","created":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T21:49:26Z","timestamp":1747172966000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A bi-objective robust optimization model to bolster a resilient medical supply chain in case of the ripple effect"],"prefix":"10.1007","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5314-8576","authenticated-orcid":false,"given":"G\u00f6khan","family":"\u00d6z\u00e7elik","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6544-7976","authenticated-orcid":false,"given":"Fatma Bet\u00fcl","family":"Yeni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7493-0639","authenticated-orcid":false,"given":"Beren","family":"G\u00fcrsoy Y\u0131lmaz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6202-4011","authenticated-orcid":false,"given":"\u00d6mer Faruk","family":"Y\u0131lmaz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,5,13]]},"reference":[{"key":"928_CR1","doi-asserted-by":"crossref","first-page":"120626","DOI":"10.1016\/j.renene.2024.120626","volume":"229","author":"P Bahmani","year":"2024","unstructured":"Bahmani P, Sadrabadi MHD, Makui A, Jafari-Nodoushan A (2024) An optimization-based design methodology to manage the sustainable biomass-to-biodiesel supply chain under disruptions: a case study. 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