A Scenario-based optimization model to design a hub network for covid-19 medical equipment management

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Abstract

The provision of medical equipment during pandemics is one of the most crucial issues to be dealt with by health managers. This issue has revealed itself in the context of the COVID-19 outbreak in many hospitals and medical centers. Excessive demand for ventilators has led to a shortage of this equipment in several medical centers. Therefore, planning to manage critical hospital equipment and transfer the equipment between different hospitals in the event of a pandemic can be used as a quick fix. In this paper, a multi-objective optimization model is proposed to deal with the problem of hub network design to manage the distribution of hospital equipment in the face of epidemic diseases such as Covid-19. The objective functions of the model include minimizing transfer costs, minimizing the destructive environmental effects of transportation, and minimizing the delivery time of equipment between hospitals. Since it is difficult to estimate the demand, especially in the conditions of disease outbreaks, this parameter is considered a scenario-based one under uncertain conditions. To evaluate the performance of the proposed model, a case study in the eastern region of Iran is investigated and sensitivity analysis is performed on the model outputs. The sensitivity of the model to changing the cost parameters related to building infrastructure between hubs and also vehicle capacity is analyzed too. The results revealed that the proposed model can produce justified and optimal global solutions and, therefore, can solve real-world problems.

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COVID-19 pandemic related supply chain studies: a systematic review

Priyabrata Chowdhury, Sanjoy Kumar Paul, Shahriar kaisar … (2021)

The global spread of the novel coronavirus, also known as the COVID-19 pandemic, has had a devastating impact on supply chains. Since the pandemic started, scholars have been researching and publishing their studies on the various supply-chain-related issues raised by COVID-19. However, while the number of articles on this subject has been steadily increasing, due to the absence of any systematic literature reviews, it remains unclear what aspects of this disruption have already been studied and what aspects still need to be investigated. The present study systematically reviews existing research on the COVID-19 pandemic in supply chain disciplines. Through a rigorous and systematic search, we identify 74 relevant articles published on or before 28 September 2020. The synthesis of the findings reveals that four broad themes recur in the published work: namely, impacts of the COVID-19 pandemic, resilience strategies for managing impacts and recovery, the role of technology in implementing resilience strategies, and supply chain sustainability in the light of the pandemic. Alongside the synthesis of the findings, this study describes the methodologies, context, and theories used in each piece of research. Our analysis reveals that there is a lack of empirically designed and theoretically grounded studies in this area; hence, the generalizability of the findings, thus far, is limited. Moreover, the analysis reveals that most studies have focused on supply chains for high-demand essential goods and healthcare products, while low-demand items and SMEs have been largely ignored. We also review the literature on prior epidemic outbreaks and other disruptions in supply chain disciplines. By considering the findings of these articles alongside research on the COVID-19 pandemic, this study offers research questions and directions for further investigation. These directions can guide scholars in designing and conducting impactful research in the field.

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Robust Optimization of Large-Scale Systems

John M. Mulvey, Robert Vanderbei, Stavros Zenios (1995)

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Reverse Logistics Network Design for Effective Management of Medical Waste in Epidemic Outbreaks: Insights from the Coronavirus Disease 2019 (COVID-19) Outbreak in Wuhan (China)

Hao Yu, Xu Sun, Wei Solvang … (2020)

The outbreak of an epidemic disease may pose significant treats to human beings and may further lead to a global crisis. In order to control the spread of an epidemic, the effective management of rapidly increased medical waste through establishing a temporary reverse logistics system is of vital importance. However, no research has been conducted with the focus on the design of an epidemic reverse logistics network for dealing with medical waste during epidemic outbreaks, which, if improperly treated, may accelerate disease spread and pose a significant risk for both medical staffs and patients. Therefore, this paper proposes a novel multi-objective multi-period mixed integer program for reverse logistics network design in epidemic outbreaks, which aims at determining the best locations of temporary facilities and the transportation strategies for effective management of the exponentially increased medical waste within a very short period. The application of the model is illustrated with a case study based on the outbreak of the coronavirus disease 2019 (COVID-19) in Wuhan, China. Even though the uncertainty of the future COVID-19 spread tendency is very high at the time of this research, several general policy recommendations can still be obtained based on computational experiments and quantitative analyses. Among other insights, the results suggest installing temporary incinerators may be an effective solution for managing the tremendous increase of medical waste during the COVID-19 outbreak in Wuhan, but the location selection of these temporary incinerators is of significant importance. Due to the limitation on available data and knowledge at present stage, more real-world information are needed to assess the effectiveness of the current solution.