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Study on multi-destination emergency scheduling model under dynamic continuous consumption

机译:动态连续消耗下的多目的地应急调度模型研究

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With the purpose to enhance efficiency and accurate of emergency dispatch, realize reasonable distribution material quantity, reduce life and property loss caused by paroxysmal emergency events, a dynamic continuous consumption emergency scheduling model is established. Some features of emergency scheduling goals are analyzed. The objective function includes minimizing earliest emergency start time and the least disaster relief participated places. Simultaneously, satisfactory degree of disaster area is also considered in the objective function. Two main categories of constraints, namely, continuous consumption, supply and demand quantity are considered. GA is employed to solve the model, and the basic implement step of GA is given in detail. To employ GA easily, the constraints are disposed with penalty function idea so that they are introduced to the fitness value. To validate the validity of GA, the multi disaster places emergency scheduling problem for dynamic and continuous consumption is abstracted. The experiment shows that by multi running, GA can get multi efficient typical solutions so as to provide significant support for decision-making of emergency scheduling. The global search capacity of GA is strong, and it is suitable to solve complex optimization problems such as emergency scheduling problem under dynamic and continuous consumption condition.
机译:为了提高应急调度的效率和准确度,合理分配物资数量,减少突发性突发事件造成的生命财产损失,建立了动态​​连续消耗应急调度模型。分析了应急调度目标的一些特点。目标功能包括最小化最早的紧急开始时间和最少的参与救灾的场所。同时,在目标函数中还考虑了灾区的满意程度。考虑了两个主要的约束类别,即连续消耗,供应和需求数量。采用遗传算法对模型进行求解,详细给出了遗传算法的基本实现步骤。为了容易地采用遗传算法,将约束与罚函数思想结合起来,以将其引入适应度值。为了验证遗传算法的有效性,抽象了动态和连续消耗的多灾区应急调度问题。实验表明,通过多次运行,遗传算法可以得到多种高效的典型解决方案,为应急调度决策提供重要支持。遗传算法的全局搜索能力强,适合解决动态和连续消耗条件下的复杂优化问题,如应急调度问题。

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