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The Consistent Vehicle Routing Problem

机译:一致的车辆路径问题

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摘要

In the small package shipping industry (as in other industries), companies try to differentiate themselves by providing high levels of customer service. This can be accomplished in several ways, including online tracking of packages, ensuring on-time delivery, and offering residential pickups. Some companies want their drivers to develop relationships with customers on a route and have the same drivers visit the same customers at roughly the same time on each day that the customers need service. These service requirements, together with traditional constraints on vehicle capacity and route length, define a variant of the classical capacitated vehicle routing problem, which we call the consistent VRP (ConVRP). In this paper, we formulate the problem as a mixed-integer program and develop an algorithm to solve the ConVRP that is based on the record-to-record travel algorithm. We compare the performance of our algorithm to the optimal mixed-integer program solutions for a set of small problems and then apply our algorithm to five simulated data sets with 1,000 customers and a real-world data set with more than 3,700 customers. We provide a technique for generating ConVRP benchmark problems from vehicle routing problem instances given in the literature and provide our solutions to these instances. The solutions produced by our algorithm on all problems do a very good job of meeting customer service objectives with routes that have a low total travel time.
机译:在小包装运输行业(与其他行业一样),公司试图通过提供高水平的客户服务来与众不同。这可以通过多种方式完成,包括在线跟踪包裹,确保按时交货以及提供住宅取件。一些公司希望其驾驶员在路线上发展与客户的关系,并让相同的驾驶员在客户需要服务的每一天的大致相同时间拜访相同的客户。这些服务要求,以及对车辆容量和路线长度的传统限制,定义了经典的受限车辆路线选择问题的一种变型,我们称其为一致的VRP(ConVRP)。在本文中,我们将问题表达为一个混合整数程序,并开发了一种基于记录到记录旅行算法的解决ConVRP的算法。我们将算法的性能与针对一组小问题的最佳混合整数程序解决方案的性能进行比较,然后将我们的算法应用于具有1,000个客户的五个模拟数据集和具有3,700个以上客户的真实数据集。我们提供了一种从文献中给出的车辆路径问题实例生成ConVRP基准问题的技术,并提供了针对这些实例的解决方案。我们的算法针对所有问题产生的解决方案在满足总行程时间短的路线的客户服务目标方面做得很好。

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