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Vehicle Routing Problem with Roaming Delivery Locations and Stochastic Travel Times (VRPRDL-S)

机译:具有漫游交货地点和随机旅行时间(VRPRDL-S)的车辆路径问题

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This paper presents an approach to model and solve the vehicle routing problem with random delivery locations and stochastic travel times (VRPRDL-S), a variant of the vehicle routing problem with random delivery locations that allows, for instance, the possibility of having a parcel delivered to the trunk of the customer’s vehicle, which can be in different locations during the same day. In the proposed model, the classical distance matrix is replaced by a matrix of probability distributions composed of the distribution of travel times between two points. Thus, the model integrates the fact that the travel time between two points is non-deterministic. This paper explores in detail a medium-sized problem and uses a combination of a Monte-Carlo method and an enhanced greedy randomized adaptive search procedure (GRASP) to find a pseudo-optimum. Moreover, the relevance of the approach is validated through a campaign test. This work intends to build on the current state of the art by proposing a new variant of the VRP and a heuristic method to solve it.
机译:本文提出了一种方法来建模和解决具有随机交付位置和随机行驶时间(VRPRDL-S)的车辆路径问题,这是具有随机交付位置的车辆路径问题的一种变体,例如,允许有包裹的可能性交付给客户的车辆后备箱,该行李箱可以在同一天位于不同位置。在提出的模型中,经典距离矩阵被概率分布矩阵代替,该概率分布矩阵由两点之间的行进时间分布组成。因此,该模型整合了两点之间的行进时间不确定的事实。本文详细探讨了一个中等大小的问题,并结合使用了蒙特卡洛方法和增强的贪婪随机自适应搜索程序(GRASP)来找到伪最优值。此外,该方法的相关性通过运动测试得到了验证。这项工作旨在通过提出VRP的新变体和启发式方法来解决此问题,从而在当前的最新技术基础上发展。

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