疏散规划中一种改进的离散粒子群算法

M. Yusoff, J. Ariffin, A. Mohamed
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引用次数: 11

摘要

在任何突发洪水疏散行动中,在被淹没地区分配车辆对于帮助消除生命损失至关重要。使用各种类型和能力的车辆将受害者疏散到救济中心。本文研究了一种组合优化方法,该方法的目标函数是向潜在淹没地区分配指定数量的车辆和最大数量的疏散人员。提出了离散粒子群优化算法(DPSO)和改进DPSO算法,并进行了实验。给出了结果并进行了比较。采用所提出的最小-最大方法的改进DPSO在所有四个测试类别中都产生了更好的性能。对大量撤离人员进行实验可以进一步提高DPSO的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Discrete Particle Swarm Optimization in Evacuation Planning
In any flash flood evacuation operation, vehicle assignment at the inundated areas is vital to help eliminate loss of life. Vehicles of various types and capacities are used to evacuate victims to relief centers. This paper examines combinatorial optimization approach with the objective function to assign a specified number of vehicles with maximum number of evacuees to the potential inundated areas. Discrete particle swarm optimization (DPSO) and improved DPSO are proposed and experimented on. Results are presented and compared. Improved DPSO with the proposed min-max approach yields better performance for all four testing categories. Experimenting on a large number of evacuees could further improve the performance of the DPSO.
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