Decomposition methods in stochastic programming

被引：5
|
作者：
Andrzej Ruszczyński
机构：
[1] University of Wisconsin-Madison,Department of Industrial Engineering
[2] Warsaw University of Technology,Department of Electronics and Computer Science
来源：
Mathematical Programming | 1997年 / 79卷
关键词：
Stochastic programming; Decomposition; Primal methods; Dual methods; Stochastic methods;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Stochastic programming problems have very large dimension and characteristic structures which are tractable by decomposition. We review basic ideas of cutting plane methods, augmented Lagrangian and splitting methods, and stochastic decomposition methods for convex polyhedral multi-stage stochastic programming problems.
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页码：333 / 353
页数：20
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