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Multi-objective fuzzy optimisation method for emergency evacuation based on hybrid intelligence algorithm under fuzzy environment

机译:模糊环境下基于混合智能算法的紧急疏散多目标模糊优化方法

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摘要

After a sudden public event, how to optimise emergency evacuation routings and enhance the response capability of emergency system is an important issue for emergency management agency. In this paper, we choose the optimal evacuation routing under fuzzy environment to make sure the injured reach the destination safely and quickly. Chance-constrained programming model of emergency evacuation routings and chance-dependent constraint programming models are setup respectively and a hybrid intelligence algorithm is designed to solve the model. The algorithm, which combines simulation technique and the genetic algorithm, produces chromosomes according to priority-based coding mode, uses simulation technique to calculate target values of chromosomes, produces a new group by using improved roulette wheel method to select chromosomes, crosses by adopting the partially matched crossover method, and uses reciprocal exchange mutation method to mutate. Finally, an example is presented to validate the feasibility of this model and the algorithm. The research result can help emergency decision-makers to find an optimal route after a sudden public event and reduce the casualties caused by transportation delays.
机译:突发公共事件后,如何优化应急疏散路径,提高应急系统的响应能力是应急管理机构的重要课题。在本文中,我们选择了模糊环境下的最优疏散路线,以确保受伤人员安全,快速地到达目的地。分别建立了应急疏散路径的机会约束规划模型和机会依赖约束规划模型,并设计了一种混合智能算法对该模型进行求解。该算法结合了模拟技术和遗传算法,根据优先级编码模式产生染色体,利用模拟技术计算染色体目标值,采用改进的轮盘法选择染色体产生新的群体,并采用遗传算法进行杂交。部分匹配的交叉方法,并使用对等交换突变方法进行突变。最后,给出一个例子来验证该模型和算法的可行性。该研究结果可帮助紧急决策者在突发公共事件后找到最佳路线,并减少运输延误造成的人员伤亡。

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