基于混合算法的需求响应公交灵活调度模型

Flexible Scheduling Model of Demand Response TransitBased on Hybrid Algorithm

需求响应公交(DRT)是一种新型的公共交通服务模式,为了使DRT理论能更贴合实际应用于低密度人口地区,提出了考虑多种车型和多种运营模式的公交灵活调度方式。首先设立车型和路径的双决策变量,并构建了考虑多种车型和多种运营模式的公交灵活调度模型;然后采用大循环小循环混合模式设计了混合遗传蚁群算法HGACO,该算法混合了最近邻搜索算法、2-opt法、目的地降维算子、遗传算法和蚁群算法;最后以揭西南部部分地区至城中心的3个时段为例进行调度。结果显示:考虑多种车型和多种运营模式的公交灵活调度模型具有经济性和可操作性,该模型可以使低密度地区的需求响应调度更加科学和经济;改进的混合遗传蚁群算法HGACO的求解能力、精度和稳定性均优于原算法,可以稳定地求得DRT灵活调度问题的较优解。

Demand response transit(DRT)serves is a new type of public transportation service mode.In order to make DRT theory more suitable for practical application in low-density population areas,a flexible bus scheduling model considering multiple vehicle types and multiple operating modes was proposed.First,dual decision variables for vehicle type and route were set up,and then a flexible bus dispatch model that considers multiple vehicle types as well as multiple operating modes was built.Then,a hybrid genetic ant colony algorithm HGACO,which is composed of nearest neighbor search algorithm,2-opt method,destination dimensionality reduction operator,genetic algorithm and ant colony algorithm,was designed using the hybrid model of“large loop and small loop”.Finally,taking the three sections from the southwest part of the city to the city center as an example for scheduling,the results show that the flexible bus dispatch model considering the multi-vehicle and multi-ple operation mode is practical and operable,and it can make DRT in low-density areas more scientific and economical.The improved hybrid algorithm HGACO is superior to the original algorithm in solution ability,accuracy and stability,and can stably obtain a better solution to the DRT flexible scheduling problem.