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Hybrid genetic algorithm for searching efficient paths in traffic assignment

机译:在交通分配中寻找有效路径的混合遗传算法

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The selection of path set has a great influence on stochastic traffic assignment. By considering path selection character of road users and traffic restriction in real road network, the concept of efficient paths is redefined. Moreover, a vertices-outdegree-based genetic algorithm (GA) is designed which adopts positive integer coding method. Furthermore, the probabilities of crossover and mutation are adjusted by adaptive algorithm and the process of selection is adopted simulated annealing algorithm to maintain the diversity and convergence of population. Thereby, this algorithm does not need to repair chromosome and can cover the shortages of priority - based GA. While finding efficient path sets of multi-OD (Origination-Destination) at the same time, this method can improve the computation efficiency by decoding simultaneously. At last, a case study is given for verifying the efficiency.
机译:路径集的选择对随机交通分配有很大的影响。通过考虑道路用户的路径选择特性和真实道路网络中的交通限制,重新定义了有效路径的概念。此外,设计了一种采用基于顶点整数的遗传算法(GA),该算法采用正整数编码方法。此外,通过自适应算法调整交叉和变异的概率,并采用模拟退火算法选择过程,以保持种群的多样性和收敛性。因此,该算法不需要修复染色体,并且可以弥补基于优先级的遗传算法的不足。在同时找到多OD(Origination-Destination)的有效路径集的同时,该方法可以通过同时解码来提高计算效率。最后,通过案例研究验证了效率。

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