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Congestion avoidance and break scheduling within vehicle routing

机译:车辆路线内的拥堵避免和中断安排

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摘要

Vehicle routing is a complex daily task for businesses such as logistic service providers and distribution firms. Planners have to assign many orders to many vehicles and, for each vehicle, assign a delivery sequence. The objective is to minimize total transport costs. These costs typically include the number of vehicles used and the total travel distance or time. Two general timing restrictions make vehicle routing particularly difficult: traffic congestion and driving hours regulations. As a result of traffic congestion, travel times depend on the time of departure. Therefore, vehicle routing also involves the subtask of optimizing each vehicle’s departure times (both from the depot and from the customers). Driving hours regulations - which pose restrictions on driving and working times (between breaks) - have to be taken into account, making departure time optimization particularly difficult. In this research, we study the Vehicle Routing Problem under time-dependent travel times and driving hours regulations. We propose a generic solution method for Vehicle Routing Problems that can handle various restrictions, such as vehicle capacities and time windows. Furthermore, we demonstrate that this method performs very well on problems which include driving hours regulations. Test results on Vehicle Routing Problems with traffic congestion are also very promising. Most delays caused by traffic congestion can be avoided by considering them when developing vehicle route plans. This is done by avoiding predictably busy areas during problematic hours. The solution methods proposed in this thesis are not limited to the problems they were initially designed for. We illustrate how they can be used in other studies, such as policy making, by analyzing vehicle routing from a distributed decision making perspective. In conclusion, there are various applications of the solution methods proposed in this thesis and they may allow for substantial improvements in practice.
机译:对于后勤服务提供商和分销公司等企业而言,车辆路线安排是一项复杂的日常任务。计划者必须为许多车辆分配许多订单,并为每辆车辆分配交货顺序。目的是使总运输成本最小化。这些成本通常包括所用车辆的数量以及总行驶距离或时间。两项一般的时间限制使车辆的选路特别困难:交通拥堵和行驶时间规定。由于交通拥堵,旅行时间取决于出发时间。因此,车辆路线选择还涉及优化每辆车的出发时间(从仓库和客户出发)的子任务。必须考虑驾驶时间规定-限制驾驶时间和工作时间(在休息之间),这使得出发时间的优化尤为困难。在这项研究中,我们研究与时间有关的旅行时间和驾驶时间规定下的车辆路径问题。我们提出了一种针对车辆路径问题的通用解决方法,该方法可以处理各种限制,例如车辆容量和时间窗口。此外,我们证明了该方法在包括行车时间规定在内的问题上的表现非常出色。关于交通拥堵的车辆路径问题的测试结果也很有希望。在制定车辆路线计划时,可以通过考虑交通拥堵而避免的大多数延误。这可以通过在出现问题的时段避免出现可预见的繁忙区域来完成。本文提出的解决方法不仅限于最初设计的问题。通过从分布式决策角度分析车辆路线,我们说明了如何将它们用于其他研究,例如政策制定。综上所述,本文提出的求解方法有多种应用,可以在实践中进行实质性的改进。

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    Kok, A.L.;

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  • 年度 2010
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