接运公交网络设计的多目标优化模型及遗传变邻域搜索求解算法

Multi-objective Model for Feeder Bus Network Design Problem Using a Genetic-variable Neighborhood Search Algorithm

为了使接运公交网络更好地为轨道交通车站集散客流服务,将其作为研究对象,提出了接运公交网络的优化方法.考虑接运公交网络服务的需求量与接运公交供给密切相关、接运公交发车时刻与轨道交通车辆到站时刻构成有序衔接,以接运公交服务的乘客量最大化、接运乘客平均成本最小化、运营成本最小化为优化目标,构建了接运公交网络的多目标优化模型.为求解模型,设计了利用产生式方法获得Pareto解集的遗传-变邻域搜索算法.将设计的遗传-变邻域搜索算法与遗传算法、精确算法分别进行比较,通过算例验证了模型与算法的有效性.

To make the feeder bus network offer passenger feeder service better for rail station, a methodology was proposed for feeder bus network optimization. The close relationship between feeder bus supply and the satisfied demand by feeder bus network, and the schedule coordination between feeder bus timetable and arrival time of rail transit station were both taken into consideration. A multi-objective programming model for feeder bus network design was proposed to maximize satisfied demand, and to minimize average user cost and operation cost. With generating approaches, a genetic variable- neighborhood-search algorithm for solving the Pareto solution set of the proposed model was given. The proposed genetic variable-neighborhood-search algorithm was compared with genetic algorithm and exact algorithm, respectively. A numerical example was given, and the proposed mathematical model and the solution algorithm were verified.