Abstract: To improve the effectiveness of the bus scheduling scheme, a model is developed by considering the average daily passenger volume of bus and the maximum and minimum departure intervals. The objective function of the model is to minimize the company’s operating costs and passenger’s waiting time. The bus scheduling is a typical NPhard problem. A differential evolution bacteria foraging optimization algorithm is then presented to solve the NPhard problem. As the velocity of the traditional bacteria foraging optimization algorithm is slow, the bacterium position is improved by differential evolution in chemotaxis process to improve the convergence precision. Based on the real traffic data of several bus lines, the model is calculated and simulated through programming. The simulation result shows that the model and the optimization algorithm can obtain the satisfaction solution more effectively.

Key words: traffic engineering, bus scheduling, bacterial foraging, differential evolution 

摘要： 为了提高公交车辆优化调度方案的有效性，考虑公交车辆平均客运量，最大、最小发车间隔等约束, 建立了以企业收益和乘客利益最大为目标的公交车辆调度模型.针对公交车调度强NP组合优化的特点，提出了一种基于差分进化细菌觅食优化算法求其有效近似解.传统细菌觅食算法优化过程速度较慢，利用差分进化方法对趋化过程中的细菌位置进行修正，增加收敛的精度.最后，结合某公交线路的数据，编程进行计算与仿真，结果表明，利用该模型及其算法能够快速得到公交发车间隔的满意解.

关键词: 交通工程, 车辆调度问题, 细菌觅食算法, 差分进化