Khalilpourazari Soheyl, Hashemi Doulabi Hossein
Department of Mechanical, Industrial & Aerospace Engineering, Concordia University, Montreal, Canada.
Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Montreal, Canada.
Ann Oper Res. 2022 Apr 21:1-26. doi: 10.1007/s10479-022-04673-9.
World Health Organization (WHO) declared COVID-19 as a pandemic On March 12, 2020. Up to January 13, 2022, 320,944,953 cases of infection and 5,539,160 deaths have been reported worldwide. COVID-19 has negatively impacted the blood supply chain by drastically reducing blood donation. Therefore, developing models to design effective blood supply chains in emergencies is essential. This research offers a novel multi-objective Transportation-Location-Inventory-Routing (TLIR) formulation for an emergency blood supply chain network design problem. We answer questions regarding strategic, operational, and tactical decisions considering disruption in the network and blood shelf-life. Since, in real-world applications, the parameters of the proposed mathematical formulation are uncertain, two flexible uncertain models are proposed to provide risk-averse and robust solutions for the problem. We applied the proposed formulations in a case study. Under various scenarios and realizations, we show that the offered robust model handles uncertainties more efficiently and finds solutions that have significantly lower costs and delivery time. To make a reliable conclusion, we performed extensive worst-case analyses to demonstrate the robustness of the results. In the end, we provide critical managerial insights to enhance the effectiveness of the supply chain.
The online version contains supplementary material available at 10.1007/s10479-022-04673-9.
世界卫生组织(WHO)于2020年3月12日宣布新冠疫情为大流行。截至2022年1月13日,全球报告了320,944,953例感染病例和5,539,160例死亡病例。新冠疫情通过大幅减少献血量对血液供应链产生了负面影响。因此,开发在紧急情况下设计有效血液供应链的模型至关重要。本研究针对紧急血液供应链网络设计问题提出了一种新颖的多目标运输-选址-库存-路径(TLIR)公式。我们回答了有关考虑网络中断和血液保质期的战略、运营和战术决策的问题。由于在实际应用中,所提出的数学公式的参数是不确定的,因此提出了两个灵活的不确定模型,为该问题提供风险规避和稳健的解决方案。我们将所提出的公式应用于一个案例研究。在各种情景和实现情况下,我们表明所提供的稳健模型能更有效地处理不确定性,并找到成本和交付时间显著更低的解决方案。为了得出可靠的结论,我们进行了广泛的最坏情况分析以证明结果的稳健性。最后,我们提供了关键的管理见解以提高供应链的有效性。
在线版本包含可在10.1007/s10479-022-04673-9获取的补充材料。