| 引用本文: | 郑乐,高良鹏,沈金星,李文权.可变线路式公交运行服务能力优化策略[J].哈尔滨工业大学学报,2021,53(9):107.DOI:10.11918/202012031 |
| ZHENG Yue,GAO Liangpeng,SHEN Jinxing,LI Wenquan.Operational service capability optimization strategies for flex-route transit service[J].Journal of Harbin Institute of Technology,2021,53(9):107.DOI:10.11918/202012031 |
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| 摘要: |
| 为了提高乘客出行需求不确定条件下可变线路式公交的运行服务能力,提出了动态离站时间窗策略以及待选站点策略两种运行优化策略。首先对策略应用背景下可变线路式公交运行方式进行了详述,并将其划分为两阶段的优化问题。然后采用混合整数规划模型对该问题进行建模,第1阶段的优化目标为最大化被服务的乘客数量,第2阶段的优化目标是最小化被接受乘客的总出行时间。针对所构建的模型,提出了一种改进的文化基因算法,对该模型进行求解。基于实际案例的仿真结果表明:两种策略从时间以及空间的维度打破了原有运行方式的固定站点离站时间约束以及乘客上下车点的空间约束,从而提高了可变线路式公交路径规划的灵活性,可以在不增加任何运营成本的情况下显著降低乘客预约请求被拒绝的比例,并且在同时应用时可以实现优势互补,至多可减少22%的乘客被拒绝率。 |
| 关键词: 交通工程 可变线路式公交 服务能力 车辆路径问题 文化基因算法 |
| DOI：10.11918/202012031 |
| 分类号:U492.2 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(7,1)； 南京邮电大学引进人才科研启动基金(NY220170) |
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| Operational service capability optimization strategies for flex-route transit service |
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ZHENG Yue1,GAO Liangpeng2,SHEN Jinxing3,LI Wenquan4
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(1. School of Modern Posts, Nanjing University of Posts and Telecommunications, Nanjing 210003, China; 2. School of Transportation, Fujian University of Technology, Fuzhou 350108, China; 3. College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, China; 4. School of Transportation, Southeast University, Nanjing 210089, China）
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| Abstract: |
| To improve the operational service capacity of flex-route transit under uncertain travel demand, a slack arrival strategy and a meeting point strategy were proposed. First, the operating mechanism of flex-route transit service under the proposed strategies was described in detail, and the process was divided into a two-stage optimization problem. Then, mixed integer programming (MIP) was employed to formulate the problem with a twofold objective: to maximize the number of accepted requests in the first stage and to minimize the total trip time of the accepted passengers in the second stage. A memetic algorithm was proposed to solve the model in a reasonable amount of time. Simulation experiments based on a real-life flex-route transit service were conducted to evaluate the proposed strategies. Results show that the two strategies, which relaxed the departure time constraints of checkpoints and the space constraints of reserved pick-up and drop-off locations, could improve the routing flexibility of flex-route transit service and significantly reduce the passenger rejection rate without any additional operating cost. Besides, when the two strategies were applied at the same time, the rejection rate could be reduced by up to 22%. |
| Key words: traffic engineering flex-route transit service capability vehicle routing problem memetic algorithm |
