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Time dependent truck routing and driver scheduling problem with Hours of Service regulations.

机译：服务时间规定中与时间相关的卡车路线和驾驶员调度问题。

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摘要

Driver fatigue is the cause of many truck crashes taking place today. In order to provide safety to the truck driver, the Federal Motor Carrier Safety Administration (FMCSA) has implemented revised Hours of Service (HOS) regulations effective on October 1st 2005. According to the revised rules, drivers should take a break of 10 consecutive hours after 11 hours of driving time or 14 hours of duty time that includes driving time and service time, such as loading and unloading cargo. This has caused a severe increase in the cost for the trucking industry which in turn hurt shippers and ultimately customers. Due to periodic shortage of truck drivers and the new HOS regulations, the problem of scheduling drivers has been aggravated. In addition to that, delays in picking/unloading at the service center and stiffer fines/penalties resulting from new HOS regulations has decreased productivity in the trucking industry.;Traffic congestion is ignored in most of the vehicle routing literature. In this Thesis, traffic congestion is modeled by using time dependent travel speed along each segment of the transportation network, which in turn changes the travel time required to reach the destination. Thus travel speed variability of different highway segments over the course of a day is explicitly considered in the evaluation of routes. A systematic way of routing vehicles to avoid traffic congestion or waiting at customer's location as well as coordinating timely mandatory breaks will improve both safety of truck transportation and efficiency of distribution supply chains.;A single truck routing model with time dependent travel times, HOS regulations, multiple delivery locations and service time windows is formulated in this Thesis. The objective is to minimize the total time required to serve a given number of customers. The components of the total time are travel time, break time, waiting time and service time at the customer nodes. A driver is not allowed to start service before the beginning of the service time window of the customer; he/she waits at the node or takes a daily break before the start of service. In addition, it has been assumed that once the driver starts service at a location he/she is not allowed to take a daily break before the completion of service. The path taken by the truck from a customer k to a customer l depends on the departure time from node k and is found by implementing the time dependent Dijkstra's algorithm that incorporates HOS regulations. An initial tour is constructed by a greedy heuristic.;Simulated Annealing (SA) metaheuristic has been applied to most of the combinatorial optimization problems. We chose SA as the solution procedure for our problem because of its ability to escape from local minima and its easy adaptability to the problem. SA accepts uphill task with certain probability which allows the heuristic to escape from local minima.;The SA heuristic is adapted to obtain near optimal solutions to our problem. The accuracy comparison was obtained by finding the optimal solution with explicit enumeration on small size problems of up to 10 customers. Our experimental results show that the heuristic gives good quality solutions (average deviation is less than 1% from the optimal objective value) in reasonable computation time. The methodology can be easily modified and adapted to more complex problems involving multiple capacitated vehicles with pickup and delivery.
机译：驾驶员疲劳是当今许多卡车撞车的原因。为了给卡车驾驶员提供安全，联邦汽车安全管理局（FMCSA）实施了修订的“服务时间”（HOS）法规，该法规自2005年10月1日生效。根据修订后的规则，驾驶员应连续休息10个小时经过11小时的行驶时间或14小时的工作时间后，包括行驶时间和服务时间，例如装卸货物。这已导致卡车运输业的成本急剧增加，进而损害了托运人并最终伤害了客户。由于卡车司机的周期性短缺和新的HOS法规，安排司机的问题变得更加严重。除此之外，由于新的居​​者有其屋条例，服务中心的取货/卸货延迟和更严厉的罚款/罚则降低了卡车运输行业的生产率。；在大多数车辆选路文献中，交通拥堵被忽略了。在本论文中，交通拥堵是通过沿交通网络各部分使用时间相关的行进速度来建模的，这反过来又改变了到达目的地所需的行进时间。因此，在评估路线时，应明确考虑一天中不同高速公路段的行驶速度变化。一种系统化的车辆路线选择方法，可避免交通拥堵或在客户所在地等待时间以及协调及时的强制性休息时间，这将提高卡车运输的安全性和配送供应链的效率。 ，本文阐述了多个交货地点和服务时间窗口。目的是使服务给定数量的客户所需的总时间最小化。总时间的组成部分是客户节点上的旅行时间，休息时间，等待时间和服务时间。在客户的服务时间窗口开始之前，不允许驾驶员开始服务；他/她在开始服务之前在节点上等待或每天休息。另外，已经假定一旦驾驶员在某个位置开始服务，就不允许他/她在服务完成之前每天休息。卡车从客户k到客户l所走的路径取决于从节点k出发的时间，并且可以通过实施与时差相关的Dijkstra算法（包含HOS规则）来找到。最初的旅程是由贪婪的启发式方法构建的。模拟退火（SA）元启发式方法已应用于大多数组合优化问题。我们选择SA作为解决问题的方法，因为它能够摆脱局部极小值，并且易于适应问题。 SA以一定的概率接受上坡任务，这使启发式方法能够摆脱局部极小值。通过对最多10个客户的小尺寸问题进行显式枚举找到最佳解决方案，从而获得了精度比较。我们的实验结果表明，该启发式算法在合理的计算时间内给出了良好的质量解决方案（与最佳目标值的平均偏差小于1％）。该方法可以轻松修改，并适应更复杂的问题，这些问题涉及具有接送能力的多辆载重车辆。

著录项

  • 作者

    Shah, Vidit Divyang.;

  • 作者单位

    Northeastern University.;

  • 授予单位 Northeastern University.;
  • 学科 Transportation.;Operations Research.
  • 学位 M.S.
  • 年度 2009
  • 页码 126 p.
  • 总页数 126
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 综合运输;运筹学;
  • 关键词

  • 入库时间 2022-08-17 11:38:25

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