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首页> 外文期刊>Operations Research: The Journal of the Operations Research Society of America >AN OPTIMIZATION ALGORITHM FOR THE VEHICLE ROUTING PROBLEM WITH TIME WINDOWS BASED ON LAGRANGIAN RELAXATION
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AN OPTIMIZATION ALGORITHM FOR THE VEHICLE ROUTING PROBLEM WITH TIME WINDOWS BASED ON LAGRANGIAN RELAXATION

机译:基于拉格朗日松弛的带时间窗的车辆路径问题的优化算法。

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摘要

Our paper presents a new optimization method for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW is a generalization of the Vehicle Routing Problem, where the service of a customer must start within a given time interval-a so-called time window. Our method is based on a Lagrangian relaxation of the constraint set requiring that each customer must be serviced. The master problem consists of finding the optimal Lagrangian multipliers and the subproblem is a Shortest Path Problem with Time Windows and Capacity Constraints. The optimal multipliers are found using a method exploiting the benefits of subgradient methods as well as a bundle method. The method has been implemented and tested on a series of well-known benchmark problems of size up to 100 customers. Our algorithm turns out to be very competitive compared to algorithms considered in the literature, and we have succeeded in solving several previously unsolved problems. [References: 26]
机译:本文提出了一种带时间窗的车辆路径问题的新优化方法(VRPTW)。 VRPTW是车辆路径选择问题的概括,客户的服务必须在给定的时间间隔(即所谓的时间窗口)内开始。我们的方法基于约束集的拉格朗日松弛,要求每个客户都必须得到服务。主要问题是找到最佳拉格朗日乘数,子问题是具有时间窗和容量约束的最短路径问题。最佳乘数是利用一种利用次梯度方法以及捆绑方法的优点的方法来找到的。该方法已在一系列众所周知的基准问题(最多可容纳100个客户)上实施和测试。与文献中考虑的算法相比,我们的算法极具竞争力,并且我们已经成功解决了一些以前未解决的问题。 [参考:26]

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