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Partition-based decomposition algorithms for two-stage Stochastic integer programs with continuous recourse

机译:具有连续追索的两阶段随机整数节目的分区分解算法

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摘要

In this paper, we propose partition-based decomposition algorithms for solving two-stage stochastic integer program with continuous recourse. The partition-based decomposition method enhance the classical decomposition methods (such as Benders decomposition) by utilizing the inexact cuts (coarse cuts) induced by a scenario partition. Coarse cut generation can be much less expensive than the standard Benders cuts, when the partition size is relatively small compared to the total number of scenarios. We conduct an extensive computational study to illustrate the advantage of the proposed partition-based decomposition algorithms compared with the state-of-the-art approaches.
机译:在本文中,我们提出了基于分区的分解算法,用于通过连续追索来解决两阶段随机整数程序的分解算法。基于分区的分解方法通过利用由场景分区引起的不精确切割(粗切)来增强经典分解方法(例如弯曲分解)。当分区大小相比,粗切成的产生比标准弯曲的弯曲变得昂贵,而与总场景的总数相对较小。我们进行了广泛的计算研究,以说明与最先进的方法相比,基于分区的分解算法的优点。

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