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Chaos-particle Swarm Optimization Algorithm and Its Application to Urban Traffic Control

机译:混沌粒子群优化算法及其对城市交通管制的应用

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Urban traffic system is a complex system in a random way. A chaos-particle swarm optimization (C-PSO) algorithm was developed through introducing logistic map in particle swarm optimization (PSO) algorithm. Several particles in the swarm were chosen to go on chaotic searching in C-PSO which performance is steady, then the problem on getting in a local best point easily in PSO was solved. The algorithm was effectively used in dealing with the optimization of signal timing to urban area traffic, and the models for optimization were developed. The experimental results for a traffic networks consisting of nine intersections show that signal timing optimization to urban traffic based on C-PSO could respectively reduce 41.6% and 12.5% of the average delay per vehicle in area based on fix cycle algorithm and genetic algorithm. The C-PSO algorithm has a wider range of applications.
机译:城市交通系统是一种随机的复杂系统。通过在粒子群优化(PSO)算法中引入逻辑图,开发了混沌粒子群优化(C-PSO)算法。群体中的几种粒子被选择在C-PSO中进行混乱搜索哪些性能稳定,然后解决了PSO中容易进入当地最佳点的问题。该算法有效地用于处理对城市地区流量的信号时序的优化,开发了优化模型。由九个交叉路口组成的交通网络的实验结果表明,基于C-PSO的城市流量对城市流量的信号定时优化可分别降低基于修复周期算法和遗传算法的面积平均延迟的41.6%和12.5%。 C-PSO算法具有更广泛的应用。

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