A hybrid algorithm for Urban transit schedule optimization
A hybrid algorithm for Urban transit schedule optimization
复制标题
城市公交时刻表优化的混合算法
DOI：
10.1016/j.physa.2018.08.017
复制
发表时间：
2018-12-15
影响因子：
3.3
通讯作者：
Qi, Yong
中科院分区：
文献类型：
--
作者：
Tang, Jinjun;Yang, Yifan;Qi, Yong
设计合理的发车时刻表是实现城市公交优先的关键环节。既能降低公交公司运营成本，又能保障乘客出行便利。本文根据公交车的历史轨迹数据估计公交车站之间的行程时间，然后结合各车站上下车的乘客数量来优化发车时刻表。此外，优化模型考虑了实际行程时间、有限容量和到达时间分布类型等约束条件，有效地综合估计了乘客的等待时间。最后，提出了一种结合遗传算法和模拟退火算法的混合算法来搜索调度模型的最优解。最后通过实例验证了模型的有效性。通过实验将该方法的优化结果与传统遗传算法的优化结果进行了比较，结果表明了该混合优化方法的优越性和可行性。(C)2018由Elsevier B.V.出版
Designing reasonable departure schedule is the key step to realize the urban transit priority. It can not only reduce the operating cost of bus company, but also guarantee convenience for passengers. This paper estimates the travel time between bus stations based on the historical trajectory data of the bus, and then combines the number of passengers get on and off at each station to optimize the departure timetable. In addition, several constraints including actual travel time, limited capacity and arrival time distribution type are considered in the optimization models to effectively and comprehensively estimate the passenger waiting time. Finally, a hybrid algorithm combining Genetic Algorithm (GA) and Simulated Annealing Algorithm (SAA) is proposed to search optimal solution in scheduling model. A case study is applied to testify the effectiveness of proposed models. In the experiments, we compare optimization results of proposed method to traditional genetic algorithms, and the results show the superiority and feasibility of the hybrid optimization approach. (C) 2018 Published by Elsevier B.V.