In emergency situations, disaster relief organizations are faced with the difficult decision of how to allocate scarce resources in an efficient manner in order to provide the best possible relief action. This paper aims to provide an analytical model that will help relief organizations in reducing human suffering following a disaster while maintaining an acceptable level of cost efficiency. A mathematical model is introduced to optimize the relief distribution problem which considers the social cost —the total sum of logistics and deprivation costs. The fuzzy nature of the deprivation cost function is addressed with possibilistic mixed integer programming with fuzzy objectives to reflect variation in deprivation costs perceptions. The model is solved using the Rolling Horizon method in a sequence of iterations. In each iteration, part of the planning horizon is modeled in detail and the rest of the time horizon is represented in an aggregated manner. The model is tested both empirically and on a case study of internal displacement in northwest Syria. Computational results showed that considering the demographic structure in affected areas and reflecting it to the deprivation cost function helped to reach better prioritization in distribution of commodities. The rolling horizon methodology is also found to be efficient in solving large scale instances and in capturing the dynamic changes in demand and supply parameters.

在紧急情况下，救灾组织面临着如何有效分配稀缺资源以提供最佳救灾行动的艰难决定。本文旨在提供一种分析模型，该模型将有助于救济组织减少灾难后的人类痛苦，同时保持可接受的成本效率水平。引入了一个数学模型来优化救济分配问题，该问题考虑了社会成本（物流和剥夺成本的总和）。剥夺成本函数的模糊性质可以通过带有模糊目标的可能混合整数规划来解决，以反映剥夺成本感知的变化。使用Rolling Horizo​​n方法在一系列迭代中求解模型。在每次迭代中 对计划范围的一部分进行了详细建模，其余时间范围则以汇总的方式表示。对该模型进行了经验检验和叙利亚西北部内部流离失所案例研究。计算结果表明，考虑到受影响地区的人口结构并将其反映在剥夺成本函数上，有助于更好地确定商品分配的优先次序。还发现滚动层方法在解决大型实例和捕获需求和供应参数的动态变化方面非常有效。计算结果表明，考虑到受影响地区的人口结构并将其反映在剥夺成本函数上，有助于更好地确定商品分配的优先次序。还发现滚动层方法在解决大型实例和捕获需求和供应参数的动态变化方面非常有效。计算结果表明，考虑到受影响地区的人口结构并将其反映在剥夺成本函数上，有助于更好地确定商品分配的优先次序。还发现滚动层方法在解决大型实例和捕获需求和供应参数的动态变化方面非常有效。