改进遗传算法在公交调度优化中的应用

摘要

在充分考虑公交公司运营成本和乘客候车等待成本的基础上,引入了乘客坐车舒适度这一指标建立了公交调度优化模型.针对基本遗传算法在实际应用中出现进化缓慢和提前收敛的问题,利用蚁群算法具有局部搜索能力强和收敛速度比较快等优点,引入了蚁群算法引导变异,建立了自适应的遗传算法,实现了模型求解的高效性和高精度.%On the basis of giving full consideration of the bus company's operating cost and the passenger's waiting cost, this paper taken the passenger's comfort degree into account to established a bus scheduling optimization model. Considering the problem of slow evolution and the early convergence in the practical application of basic Genetic Algorithm, it uses the advantages of stronger local search ability and faster convergence speed in Ant Colony Algorithm to build an adaptive Genetic Algorithm. Experiments show that it achieved the efficient and high-precision in the model solution of bus scheduling.