Partition-based decomposition algorithms for two-stage Stochastic integer programs with continuous recourse
Partition-based decomposition algorithms for two-stage Stochastic integer programs with continuous recourse
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DOI：
10.1007/s10479-017-2689-7
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发表时间：
2020-01
影响因子：
4.8
通讯作者：
B. S. Pay;Yongjia Song
中科院分区：
文献类型：
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作者：
B. S. Pay;Yongjia Song
本文提出了求解具有连续资源的两阶段随机整数规划的基于划分的分解算法。基于划分的分解方法通过利用场景划分产生的不精确割集(粗割集)来增强经典的分解方法(如Bders分解)。当分区大小与方案总数相比相对较小时，生成粗切割的成本可能比标准弯曲切割低得多。我们进行了大量的计算研究，以说明所提出的基于划分的分解算法与最先进的方法相比的优势。
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.