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Positive point charge potential field based ACO algorithm for multi-objective evacuation routing optimization problem

机译:基于正电荷点势场的ACO算法求解多目标疏散路径优化问题

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Multi-objective evacuation routing optimization problem is defined to find out optimal evacuation routes for a group of evacuees according to multiple evacuation objectives. For improving the evacuation efficiency, we abstracted the evacuation zone as a positive-point-charge-potential-field-like model (PPCPF-like model), and we proposed PPCPF-ACO algorithm to solve this problem based on the proposed model. In PPCPF-ACO algorithm, we use non-dominated sorting based roulette wheel routing method (NSRWR) to further improve evacuation efficiency. In Wuhan Sports Center case, we compared PPCPF-ACO with HMERP-ACO (hierarchical multi-objective evacuation routing problem - ant colony optimization) and traditional ACO according to three evacuation objectives, namely, total evacuation time, total evacuation route length and cumulative congestion degree. The experimental results show that PPCPF-ACO has a better performance than HMERP-ACO algorithm and traditional ACO algorithm while solving multi-objective evacuation routing optimization problem.
机译:定义了多目标疏散路径优化问题,以根据多个疏散目标找到一组疏散人员的最佳疏散路径。为了提高疏散效率,我们将疏散区抽象为正电荷类似势场模型(PPCPF类模型),并在此模型的基础上提出了PPCPF-ACO算法来解决该问题。在PPCPF-ACO算法中,我们使用基于非支配排序的轮盘赌路由方法(NSRWR)来进一步提高疏散效率。在武汉体育中心案例中,我们根据总疏散时间,总疏散路径长度和累积拥堵三个三个疏散目标,将PPPCF-ACO与HMERP-ACO(分层多目标疏散路由问题-蚁群优化)和传统ACO进行了比较程度。实验结果表明,在解决多目标疏散路径优化问题的同时,PPPCF-ACO具有比HMERP-ACO算法和传统ACO算法更好的性能。

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