基于NSGA算法的公交车辆调度优化模型

公交车辆调度方案的优化对于提高公交服务水平,促进公交事业的快速发展至关重要.在乘客与公交公司利益博弈的基础上,基于极小极大思想,考虑公交车车辆容量的限制及城市道路信号控制的干扰因素,建立公交发车间隔优化模型,并利用非支配排序遗传算法(NSGA)进行模型的求解.以河南省焦作市的公交线路为例进行验证,优化结果显示乘客的平均等车时间相对减少48.3%,公交车的全日平均满载率下降了3.8%,公交服务水平有所改善.

Bus Scheduling Optimization Model Based on NSGA Algorithm

Optimized buses scheduling scheme is essential to improve transit service levels and promote rapid development of public transport. On the basis of the interests of game between passengers and the bus company, considering bus vehicle capacity constraints and confounding factors of urban road signal control, we have built the bus departure interval optimization model based on the Minimax ideas , and then use the non-dominated Sorting Genetic Algorithm (NSGA) to solve the model. Illustrated by the case of bus lines in Jiaozuo,Henan Province, the transit service levels have been improved with the optimization results show that the average waiting time of passengers relative reduced by 48.3% and buses full day average load factors fell by 3.8%.