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A multi population memetic algorithm for the vehicle routing problem with time windows and stochastic travel and service times

机译:具有时间窗和随机行驶与服务时间的车辆路径问题的多种群模因算法

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This paper presents a new model to solve the Vehicle Routing Problem with Time Windows and Stochastic Travel and Service Times. The model allows ensuring service levels at the solution, on depot’s time window, and at each client. The problem is solved via a Multi Population Memetic Algorithm where each population tackles the problem using a different strategy while sharing information across the populations. The solution approach is tested on modified instances proposed by Solomon for the deterministic counterpart. Preliminary results show that the proposed method guarantees a high service level with an increase of 29.65% on the fleet size when comparing with the best deterministic solution found.
机译:本文提出了一种新的模型来解决带有时间窗和随机行驶与服务时间的车辆路径问题。该模型可确保在解决方案,软件仓库的时间窗口以及每个客户处确保服务水平。通过多种群模因算法解决了该问题,其中每个种群使用不同的策略解决问题,同时在各个种群之间共享信息。解决方案方法在所罗门为确定性对应项提出的修改实例上进行了测试。初步结果表明,与找到的最佳确定性解决方案相比,该方法可确保较高的服务水平,机队规模增加29.65%。

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