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Multiobjective Optimization of Evacuation Routes in Stadium Using Superposed Potential Field Network Based ACO

机译:基于ACO叠加势场网络的体育场馆疏散路径多目标优化

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摘要

Multiobjective evacuation routes optimization problem is defined to find out optimal evacuation routes for a group of evacuees under multiple evacuation objectives. For improving the evacuation efficiency, we abstracted the evacuation zone as a superposed potential field network (SPFN), and we presented SPFN-based ACO algorithm (SPFN-ACO) to solve this problem based on the proposed model. In Wuhan Sports Center case, we compared SPFN-ACO algorithm with HMERP-ACO algorithm and traditional ACO algorithm under three evacuation objectives, namely, total evacuation time, total evacuation route length, and cumulative congestion degree. The experimental results show that SPFN-ACO algorithm has a better performance while comparing with HMERP-ACO algorithm and traditional ACO algorithm for solving multi-objective evacuation routes optimization problem.
机译:定义了多目标疏散路线优化问题,以找出在多个疏散目标下一组疏散人员的最佳疏散路线。为了提高疏散效率,我们将疏散区域抽象为一个叠加的势场网络(SPFN),并在此模型的基础上提出了基于SPFN的ACO算法(SPFN-ACO)来解决此问题。以武汉体育中心为例,在总疏散时间,总疏散路径长度和累积拥堵度这三个疏散目标下,将SPFN-ACO算法与HMERP-ACO算法和传统ACO算法进行了比较。实验结果表明,SPFN-ACO算法与HMERP-ACO算法和传统ACO算法相比,具有更好的解决多目标疏散路径优化问题的性能。

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