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A Bi-level Multi-objective Programming Model for Bus Crew and Vehicle Scheduling

机译:公共汽车机组和车辆调度的双级多目标规划模型

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This paper focuses on the analysis of bus crew and vehicle scheduling under the management system commonly-seen in China. With considerations of management rules in practice and related regulations in China, this study proposes a bi-level multi-objective programming model for optimizing the crew and vehicle scheduling for the operation of public bus system. The developed model first estimates the lower bound of the global minimum number of drivers and buses needed in each week. The upper-level model minimizes the difference between the solution and the estimated lower bound and determine the number of vehicles needed; and then the lower-level model tries to minimize the number of drivers needed in each day. A branch and bound solution method has been developed to solve the proposed NP-Hard model, and has been programmed to achieve the computer aided crew and vehicle scheduling. A case study based on four different timetables demonstrated that the estimated lower bounds are with 13% of the global optimization that can ben achieved by the proposed approach. The implementation of the developed method can efficiently reduce the operation cost and support the automated intelligent scheduling for the Advanced Public Transportation System.
机译:本文重点介绍了在中国常见的管理系统下的公共汽车机组人员和车辆调度分析。考虑到中国实践中的管理规则和相关规定,本研究提出了一种用于优化公共汽车系统运营的机组人员和车辆调度的双层多目标规划模型。开发模型首先估计每周所需的全球最小驱动因素和公共汽车的下限。上层模型最小化解决方案与估计的下限之间的差异,并确定所需的车辆数量;然后,较低级别的模型试图最小化每天所需的驱动器数量。已经开发了一个分支和绑定的解决方案方法来解决所提出的NP硬模型,并被编程为实现计算机辅助机组人员和车辆调度。基于四个不同时间表的案例研究表明,估计的下限是通过拟议方法实现的全球优化的13%。开发方法的实现可以有效地降低运营成本并支持高级公共交通系统的自动智能调度。

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