In order to address the lack of collaborative decision and failure to notice the emergency and fairness of relief after disasters have occurred, a collaborative decision-making system for emergency relief materials dispatching is established. According to the forecast of the demand for postdisaster relief materials, the entropy weight-TOPSIS method is applied to measure the urgency of the disaster area; then, a “Hub-and-Spoke” dispatching network is constructed. In this paper, a multiobjective collaborative relief material dispatching model is built, which has great performance in terms of minimal distribution cost and maximal fairness, and the objective of fairness requires minimizing the penalty cost caused by unsatisfied demands. Based on the urgency of demand points, the simulated annealing algorithm is designed to solve the Pareto disaggregation of multiobjective optimization model. The performance of the model is verified with the case of Wenchuan Earthquake. The results indicate that if the fair distribution of supplies is emphasized, it will increase the number of rescue vehicles and the number of distribution batches. On the other hand, a variety of relief material dispatching plans can be provided based on calculation of the Pareto front for policy-makers.

中文翻译：

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基于紧急度的救灾物资协同调度建模与仿真

为了解决灾害发生后缺乏协作决策，无法及时通知救灾紧急情况和公正性的问题，建立了应急救灾物资调度协作决策系统。根据对灾后救灾物资需求的预测，采用熵权-TOPSIS法测度灾区的紧急程度。然后，建立了“中心辐射”调度网络。本文建立了一种多目标协同救灾物资调度模型，该模型在最小的分发成本和最大的公平性上具有良好的性能，而公平的目标要求将不满意的需求所导致的惩罚成本最小化。根据需求点的紧迫性，设计了模拟退火算法以解决多目标优化模型的帕累托分解。以汶川地震为例验证了模型的性能。结果表明，如果强调物资的公平分配，将会增加救援车辆的数量和分配批次的数量。另一方面，可以根据决策者对帕累托阵线的计算，提供各种救济物资分发计划。