The city bus line network optimization problems were researched. In order to solve the urban public transport planning issues, the efficiency of urban traffic should be improved. Due to the the stability of traditional genetic algorithm of bus lines is not high, an improved genetic algorithm was proposed as the bus route network optimization model. The fitness function of genetic algorithm and the constraints were constructed, and the effective population initialization algorithm was established. The model used an improved genetic algorithm to resolve the optimization model, that is, the priority encoding and multi-chromosome structure were added to the traditional genetic algorithm . Simulation results show that compared with the traditional genetic algorithm, the improved algorithm can effectively increase the speed of the search path, which verifies the practicability and effectiveness of the algorithm.%研究了城市公交线路网优化问题.由于公交车的容量、耗时、站点配置等问题,传统的遗传算法在公交线路网优化中的运行效率不高等.为提高公共交通车辆调度效率,提出了改进的遗传算法公交线路网优化模型,保证公交公司不亏损和乘客乘车成本两者前提下,构造了遗传算法适应度函数以及约束条件,并建立有效的初始化算法种群,从而建立新的公交线路网优化模型,在求解模型过程中,采用了改进的遗传算法求解优化模型,即在传统遗传算法中加入了优先级编码方式以及多染色体结构.仿真结果表明改进算法的可行性,并与传统的遗传算法相比,算法种群的整体性能要优于传统的遗传算法,对提高遗传算法的运行效率有较高的作用.
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