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A Rolling Horizon Model to Optimize Aerodynamic Efficiency of Intermodal Freight Trains with Uncertainty

机译:具有不确定性的优化联运列车空气动力学效率的滚动视野模型

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Aerodynamic efficiency of intermodal freight trains can be significantly improved by minimizing the adjusted gap lengths between adjacent loads. This paper first develops a static model to optimize load placement on a sequence of intermodal trains that have scheduled departure times. This model applies when full information on all trains and loads is available. Then, we develop a dynamic model to account for the more realistic situation in which there is incomplete or uncertain information on future trains and incoming loads. This paper develops methodology to balance between (i) the advantage from optimizing multiple trains together and (ii) the risk of making suboptimal decisions due to incomplete future information. We propose a rolling horizon scheme to address this challenge, where exponentially decreasing weights are assigned to the objective functions of future trains. Numerical results based on empirical data show significant aerodynamic efficiency benefits from these optimization models.
机译:通过最小化相邻载荷之间的调整间隙长度,可以显着提高联运货运列车的空气动力学效率。本文首先开发了一个静态模型,以优化在安排了发车时间的一系列联运列车上的负载位置。当可获得所有列车和负荷的完整信息时,将应用此模型。然后,我们开发一个动态模型来考虑更现实的情况,在这种情况下,有关未来火车和传入负载的信息不完整或不确定。本文开发了一种方法,可以在(i)一起优化多列火车的优势与(ii)由于未来信息不完整而做出次优决策的风险之间取得平衡。我们提出了一种滚动视野方案来应对这一挑战,其中权重呈指数递减的形式分配给了未来列车的目标功能。基于经验数据的数值结果表明,这些优化模型显着提高了空气动力学效率。

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