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Multi-mitigation strategies in medical supplies for epidemic outbreaks.
Zhang, Yuwei; Li, Zhenping; Zhao, Yuwei.
  • Zhang Y; School of Information, Beijing Wuzi University, Beijing, China.
  • Li Z; School of Information, Beijing Wuzi University, Beijing, China.
  • Zhao Y; School of Economics and Management, Beijing University of Chemical Technology, Beijing, China.
Socioecon Plann Sci ; 87: 101516, 2023 Jun.
Artículo en Inglés | MEDLINE | ID: covidwho-2237544
ABSTRACT
The outbreak of Coronavirus disease 2019 (COVID-19) highlights the importance of sufficient medical supplies stockpiling at the pre-event stage. In contrast, the potential disadvantages of maintaining adequate items at strategic locations (i.e., reserves) are considerable inventory-related costs. Unpredicted demand leads to a high degree of uncertainty. Efforts to mitigate the uncertainty should rely not only on prepositioning supplies at reserves but also on integrating various channels of medical materials. This paper proposes multi-mitigation strategies in medical supplies to ensure uninterrupted supply for hospitals and significant savings by introducing two-type suppliers, reserving and manufacturing suppliers. Thus, each hospital with uncertain demand is enabled to be served by various channels during pandemics prepositioning in reserves, backups served by reserving suppliers, and medical commodities produced by manufacturing suppliers. Stochasticity is also incorporated into the raw materials available to produce. This research aims to develop an emergency response application that integrates preparedness action (reserve location, inventory level, and contract supplier's selection) with post-event operations (allocating medical materials from various channels). We formulate a two-stage stochastic mixed integer program to determine prepositioning strategy, including two-type suppliers' selection, and post-event allocation of multiple sources. A branch-and-Benders-cut method is developed for this problem and significantly outperforms both the classical Benders decomposition and Gurobi in the solution time. Different-sized test instances also verify the robustness of the proposed method. Based on a realistic and typical case study (inspired by the COVID-19 pandemic in Wuhan, China), significant savings, an increase in inventory utilization and an increase in demand fulfilment are obtained by our approach.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Idioma: Inglés Revista: Socioecon Plann Sci Año: 2023 Tipo del documento: Artículo País de afiliación: J.seps.2023.101516

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Idioma: Inglés Revista: Socioecon Plann Sci Año: 2023 Tipo del documento: Artículo País de afiliación: J.seps.2023.101516