Abstract In the United States, natural disasters have seriously affected the country’s economy as well as people. They have also been challenging the country’s emergency response capacity. In order to reduce the damage caused by disasters, there is a need for the proper planning and efficient management of relief supplies in place before the onset of a disaster. This paper proposes to integrate the decision making of supplier selection into the preparedness stage in responding to disasters for timely distribution of relief supplies. Agreement terms including the commitment quantity of the relief agency, the reserve capacity of the suppliers, and the quantity discount rate are considered. Compared to the traditional two-stage stochastic programming approach, which is commonly used in the field of humanitarian logistics, a multi-stage stochastic programming model is presented because of the stochastic nature of the proposed problem, and the need to make sequential decisions over time. In this research, a real-world setting which considers disasters such as earthquakes, floods and hurricanes in the mainland United States is used as a case study. The sensitivities of the model for variation of parameters are also studied. This paper provides the relief agencies insights on how the agreement terms affect the supplier selection decision, and how the total expected costs of having an agreement in place and procuring relief items from the suppliers can be minimized.

中文翻译：

---

灾难响应中的供应商选择决策

摘要 在美国，自然灾害严重影响了国家的经济和人民。他们还一直在挑战该国的应急响应能力。为了减少灾害造成的损失，需要在灾害发生之前对救援物资进行适当的规划和有效的管理。本文提出将供应商选择的决策纳入应对灾害的准备阶段，以便及时分配救灾物资。协议条款包括救济机构的承诺数量、供应商的储备能力和数量折扣率。与人道主义物流领域常用的传统两阶段随机规划方法相比，由于所提出问题的随机性，以及随着时间的推移做出连续决策的需要，提出了一个多阶段随机规划模型。在这项研究中，考虑了美国大陆地震、洪水和飓风等灾害的真实世界环境被用作案例研究。还研究了模型对参数变化的敏感性。本文为救援机构提供了有关协议条款如何影响供应商选择决策的见解，以及如何最大限度地减少签订协议和从供应商处采购救援物品的总预期成本。考虑了美国大陆地震、洪水和飓风等灾害的真实世界环境被用作案例研究。还研究了模型对参数变化的敏感性。本文为救援机构提供了有关协议条款如何影响供应商选择决策的见解，以及如何最大限度地减少签订协议和从供应商处采购救援物品的总预期成本。考虑美国大陆地震、洪水和飓风等灾害的真实世界环境被用作案例研究。还研究了模型对参数变化的敏感性。本文为救援机构提供了有关协议条款如何影响供应商选择决策的见解，以及如何最大限度地减少签订协议和从供应商处采购救援物品的总预期成本。