论文部分内容阅读
为了提高公交车辆在换乘站点处的衔接效率,需要统筹考虑线网布局与时刻表编制。根据公交线网运营模式特征,研究了线网协调控制对发车间隔和出行时间优化的影响。以企业盈利最大和乘客出行时间成本最小为目标,构建了多目标区域公交时刻表模型。采用遗传算法、粒子群优化算法和遗传粒子群优化算法求解了模型。结合公交实例调查数据对该模型进行了检验。结果表明:模型目标均能有效收敛,且遗传粒子群优化算法在求解此类问题时比遗传算法及粒子群优化算法具有更高的精度和效率。实际中需要根据给定的企业运营效益和乘客出行时间成本权重值选定时刻表优化方案。
In order to improve the convergence efficiency of bus at transfer station, it is necessary to consider the layout of network and schedule preparation. According to the characteristics of bus network operation mode, this paper studies the influence of wire net coordination control on the departure interval and travel time optimization. With the goal of maximizing corporate profits and minimizing the travel time of passengers, a multi-objective regional bus schedule model is constructed. The genetic algorithm, particle swarm optimization algorithm and genetic particle swarm optimization algorithm were used to solve the model. The model was tested with the bus survey data. The results show that the model objective can effectively converge, and the genetic particle swarm optimization algorithm has higher accuracy and efficiency than GA and PSO in solving such problems. In practice, we need to select the schedule optimization scheme according to the given enterprise operating benefit and passenger travel time cost weight value.