: 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．