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Bus and driver scheduling with mealtime windows for a single public bus route

机译:公共汽车和司机调度与单一公共巴士路线的膳食时间窗户

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This study deals with the bus & driver scheduling problems with mealtime windows for a single public transport bus route. Firstly, we develop three explicit Integer Linear Programming (ILP) models to formulate: the bus driver scheduling, bus & driver scheduling, and bus & driver scheduling with mealtime windows, respectively. These ILP models enable bus operators to solve their bus & driver scheduling problems by directly invoking an available optimization solver such as IBM ILOG CPLEX. However, our numerical experiments do not show remarkable improvements, as CPLEX takes more than 12, 17, and 35 h respectively to reduce the optimality gap to at most 0.5% for solving the above three models in an over 12-hour bus & driver scheduling problem. To improve the computational efficiency, we develop a valid inequality approach that can generate valid cuts incorporating with the CPLEX. An investigation into the valid inequality approach proves its high computational efficiency. In addition, we develop a self-adaptive search method for determining the upper and lower bounds of driver group and bus fleet sizes. Finally, we test our models and approaches on a real round-trip bus route. The results indicate that compared with the only use of CPLEX to solve the above three models, the valid inequality approach can address large-scale instances in a reasonable CPU time.
机译:本研究涉及单一公共交通总线的膳食窗口的总线和司机调度问题。首先,我们开发三个显式整数线性编程(ILP)模型来制定:总线驱动程序调度,总线和驱动程序调度以及与DISTIME Windows的总线和驱动程序调度。这些ILP模型使总线运营商能够通过直接调用可用的优化求解器(如IBM ILOG CPLEX)来解决其总线和驱动程序调度问题。然而,我们的数值实验并没有显示出显着的改进,因为CPLEX分别超过12,17和35小时,以将最优值差距降低至最多0.5%,以便在超过12小时的总线和驱动程序调度中解决上述三种模型问题。为了提高计算效率,我们开发了一个有效的不等式方法,可以生成与CPLEX的有效剪辑。对有效不等式方法的调查证明了其高计算效率。此外,我们制定了一种自适应搜索方法,用于确定驱动器组和总线舰队尺寸的上限和下限。最后,我们在真正的往返巴士路线上测试我们的模型和方法。结果表明,与唯一使用CPLEX来解决上述三种模型相比,有效的不等式方法可以在合理的CPU时间内解决大规模的实例。

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