This paper presents a bi-level blood supply chain network under uncertainty during the COVID-19 pandemic outbreak using a Stackelberg game theory technique. A new two-phase bi-level mixed-integer linear programming model is developed in which the total costs are minimized and the utility of donors is maximized. To cope with the uncertain nature of some of the input parameters, a novel mixed possibilistic-robust-fuzzy programming approach is developed. The data from a real case study is utilized to show the applicability and efficiency of the proposed model. Finally, some sensitivity analyses are performed on the important parameters and some managerial insights are suggested.

本文介绍了在 COVID-19 大流行爆发期间使用 Stackelberg 博弈论技术在不确定性下的双层血液供应链网络。开发了一种新的两阶段双层混合整数线性规划模型，其中总成本最小化并且捐助者的效用最大化。为了应对某些输入参数的不确定性，开发了一种新颖的混合可能性-鲁棒-模糊规划方法。来自真实案例研究的数据被用来展示所提出模型的适用性和效率。最后，对重要参数进行了一些敏感性分析，并提出了一些管理见解。