中文摘要：

考虑到应急情况下信息的不完备性和可更新性,以及应急资源配置的复杂性、动态性和序贯性等特点,灾害应急资源配置决策需要综合运用灾害历史信息和样本信息,这是一个＂观测-决策-配置＂的多阶段序贯决策过程.以随机变量的形式记录道路损毁率的历史信息和样本信息,并在此基础上计算应急情况下的资源运输时间.在根据公平原则确定各受灾点资源配置量的基础上,应用贝叶斯分析、最优化理论等对基于道路损坏率信息更新的应急资源＂观测-决策-配置＂序贯决策问题进行系统建模,并设计基于矩阵编码的遗传算法进行求解.通过数值仿真验证了模型和算法的有效性,结果表明：灾害样本信息和历史信息是应急资源配置决策的重要基础,道路损坏率信息在决策过程中起着重要作用.应急救援决策者可以通过输入相关数据来获取具体的应急资源配置方案.

英文摘要：

Considering that the information in emergency situation is usually not complete and is updated every second,and that resources allocation planning in natural disasters is complicated,dynamic,and sequential,both historical and current sample information need to be used to make effective plans in emergency resources allocation planning.Therefore,resources allocation in natural disasters is a multi- phase process of＂sampling-planning-dispatching＂.By using a random variable to record the historical and sample information of the road affected level,a concept of transportation time cost due to logistics processes under emergency conditions was proposed.The allocation amount of each affected area was decided by the equity principle.On the base of this,and by using Bayesian analysis theory and optimization theory,an information update based sequential approach of＂sampling-planning-dispatching＂model was proposed to solve the emergency resources allocation planning problem.In addition,a matrix-coding-based genetic algorithm was developed to solve the model.Finally,a simulation study was conducted to verify the efficiency and effectiveness of the proposed methodology.The simulation results show that the sample information and historical information of disaster are very important in emergency resources allocation planning,and the information of the road affected level plays a key role in the decision-making process. The emergency decision maker can obtain a specific resources allocation plan by inputting correlative data.