考虑时间窗的定制公交线路时空分层优化模型

研究定制公交线网布局及调度优化对增强公交系统吸引力, 提高乘客出行效率具有重要意义。针对定制公交乘客需求点在时间和空间上分布离散的特点, 构建了考虑时间窗的定制公交时空分层优化模型, 并设计遗传算法对模型进行求解。通过渔网与核密度分析对需求点在时间和空间上进行了热点识别, 并实现热点区域聚类分析以及合乘站点分类。基于合乘站点集合, 综合考虑公交容量、线路长度、乘客出行距离构建了线路空间优化模型, 以乘客的时间花费最小作为优化目标构建了线路时间优化模型。以济南市城区定制公交为例对模型的性能进行评估, 案例结果表明: 模型优化后的线路方案, 乘客平均服务覆盖率可达96%, 服务区域内每个时段的单个乘客的平均节省时间为15 min, 公交的平均满载率为90%。 

A Hierarchical Spatiotemporal Optimization Model of Customized Bus Routes Considering Time Windows

Studying the layout and scheduling optimization of a customized bus line network has important implications, enhancing the attractiveness of the public transport system and passenger travel. However, the distribution of customized bus passengers' demand points in time and space is discrete, which hinders the bus line design. A timespace hierarchical optimization model of customized buses considering time windows is constructed to solve this problem, and a genetic algorithm is designed to solve the model. The hot spots of demand points are identified in time and space by analyzing the fishing net and kernel density, with the cluster analysis of hot spots and the classification of bus pooling realized. Based on the set of bus pooling, a space optimization model of bus lines is constructed by the bus capacity, line length, and passenger travel distance. A time optimization model of bus lines is constructed by the minimum time cost of passengers. Jinan customized bused are used to evaluate the performance of the model. The results show that the routing scheme is optimized by the model, with an average service coverage rate of passengers of 96%, the average travel time saved by the single passenger in each period of the service area of 15 minutes, and an average load factor of public transport of 90%.