解决城市交通局部拥挤的最佳途径是进行路径引导,其核心理论是实时动态交通分配。针对这类模型变量多、维数大以及约束条件多等局限性,本文提出了一种以量子进化方法作为路网的交通均衡分配的主要优化方法,以整个交通网络中各条出行路径的总出行时间最小为优化目标的动态交通分配模型的求解方法。仿真实验结果证实了利用量子进化求解动态交通分配问题的有效性与合理性。%The best way to reduce traffic congestion in cities is route bution. In allusion to the limitations of the sort of models, such as guidance, and its key theory is realtime dynamic traffic distil multiple variables, large dimensions and large quantity of con straints, a novel approach that takes quantum evolutionary algorithm as the major optimization method for dynamic traffic distribution model and whose optimal target is the least cost among each of the routes is proposed is this paper. This solution based on quantum evolutionary ＇algorithm is oroved valid and rational.
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