Abstract:

In order to accurately measure the social benefits of the interaction between passenger trips and enterprise operation in the optimization of bus regional timetable, a bi- level programming model for bus timetabling was developed that considers stochastic passenger emand and operating efficiency. The interaction between stochastic passenger flow demand and timetable were first analyzed, from the view of the passenger demand and service quality of bus timetables. The passenger demand was refined hierarchically, and was taken as the input of the lower- level traffic network flow model with elastic demand. With the relationships between passenger demand, travel efficiency and enterprise operation cost, the operating efficiency of bus regional timetable was taken as the objective of the upperlevel model. Finally, the Dial- MSA and genetic algorithm were used to solve this proposed bi- level programming model. The numerical results show that the operating efficiency of the optimized timetable is improved by 7.3%. The optimized bus regional timetable can better match the passenger demand, effectively improve the operating efficiency, and achieve superior dynamic adaptability.

Key words: urban traffic, regional timetable optimization, bi-level programming, operating efficiency, stochastic passenger flow demand

摘要：

为准确计量公交区域时刻表优化过程中，客流出行与企业运营博弈产生的社会效益，构建兼顾随机客流需求和时刻表运行能效的双层规划模型。从公交乘客出行量与质的角度，分析随机客流需求与时刻表之间的互动关系；依据出行性质将客流需求分层细化，作为下层弹性需求交通网络流模型的输入；考虑客流需求、乘客出行效率及企业运营成本间的波动关系，设计公交区域时刻表运行能效作为上层模型的优化目标；采用Dial-MSA与遗传算法求解双层规划模型。实例计算结果表明，优化后的公交区域时刻表运行能效提高了7.3%。可见，优化后的公交区域时刻表更能满足客流需求，有效地提高时刻表运行能效，更好地实现动态适应性。

关键词: 城市交通, 区域时刻表优化, 双层规划, 运行能效, 随机客流需求