针对大规模突发事件的可持续应急资源调度问题研究

There are always large-scale emergency affecting and threatening our society, environment, economic or even lifecycle. The fast and efficient emergency resources dispatching is an important to decrease the economic loss and casualty. At the same time, in the whole implement process, the emergency resources dispatching consume not only resources, but produce a great deal of negative effects on the environment and socio-economic, this contraries to the principles of sustainable development. Therefore, it is very important to study the sustainable dispatching problems for large-scale emergency. On the basis of the characteristics of large-scale emergencies, this project aims to quantitative analysis sustainable emergency resource dispatching problems by the optimization theory and artificial intelligent algorithm, and produce the optimization models and algorithms. According to the wide-affected area and large demand of large-scale emergency, the multilevel emergency dispatching model with resource constraint will be established. Considering the environment factor, on the basis of multi-stage and uncertainty, the multi-stage emergency resource dispatching model with environment constraint will be built. Considering the socio-economic factor, for the comprehensive and systematic, the multi-objective emergency resource dispatching model with socio-economic constrain will be presented. Through this research, this project provides theoretical basis and methods for sustainable emergency resource dispatching.

不断发生的大规模突发事件正侵袭着人类生存的社会、环境、经济甚至生命，快速、高效的应急资源调度成为减少人员伤亡、降低经济损失的重要手段。同时，应急资源调度在其实施过程中不仅消耗了大量的资源，对环境与社会经济也造成了极大的负效应，这违背了可持续发展的原则。因此，研究针对大规模突发事件的可持续调度问题显得尤为重要。本项目拟从大规模突发事件的特征出发，利用最优化理论与人工智能算法定量分析可持续应急资源调度问题，建立优化模型，并给出求解算法。针对大规模突发事件受灾面积广、应急资源需求量大的特点，建立基于资源约束的多层应急调度模型；针对大规模突发事件的阶段性和不确定性特点，考虑环境问题，建立基于环境约束的多阶段应急资源调度模型；针对大规模突发事件的综合性和系统性特点，考虑社会经济因素，建立基于社会经济约束的多目标应急资源调度模型。通过上述研究，为可持续应急资源调度提供理论基础与方法指导。

大规模突发事件不断危害人类的生命财产安全和社会生态环境。为了有效地降低突发事件对人类社会的危害，本项目首先针对受灾区域广、应急资源需求量大等特点，研究了应急环境下的资源调度与设施选址问题，建立了不确定选址集合覆盖模型和不确定最大覆盖选址模型。其次，本项目针对应急响应的多阶段性，从环境可持续性发展角度，以响应时间、应急费用和二氧化碳排放量为目标建立了不确定多目标选址-路径规划模型。为了对模型求解，设计了基于不确定模拟和遗传算法的混合智能算法。最后，从社会经济因素角度，本项目研究了多物品立体运输问题。以运输费用最小化为目标，分别建立了期望值规划模型和机会约束规划模型。利用逆不确定分布的性质讨论了模型的等价型，从而找到了模型的求解方法。此外，本项目还研究了不确定网络中的匹配问题与连通性问题，这些问题的研究进一步丰富了应急管理理论。