基于快速需求响应的城市公交在线调度方法研究

通过研究制约公交系统运行效率的问题,提出了一种旨在快速响应乘客出行需求的"小粒度"频繁调度方法,构建了以"小粒度"时段为调度周期的多日标优化模型.针对模型特征设计了实现在线调度的改进遗传算法,结合启发信息控制变异位置、增加修复算子,解决了染色体变长和跨维搜索难题.利用仿真试验验证了方法的有效性,结果表明,算法能在较短时间产生调度方案,满足在线调度要求;与传统的基于统计数据的调度方案相比,模型能有效优化出行成本和运营成本.

Study on On-line Scheduling Method of Urban Public Transport Based on Quick Response to Passengers' Needs

In order to address variable passengers' needs quickly,a multi-objective optimal model was established,which would produce timetables for buses frequently in a short period of time on the assumption that passengers' needs have been obtained through ITS.And an advanced genetic algorithm was designed to solve the program on-line.The simulation shows that a dispatching plan can be worked out in a short time with the proposed model and algorithm,the effects are better compared to those took by traditional stati...