Decomposition methods in stochastic programming

被引：130

作者：

Ruszczynski, A

机构：

[1] Department of Industrial Engineering, University of Wisconsin-Madison, Madison, WI 53706

来源：

MATHEMATICAL PROGRAMMING | 1997年 / 79卷 / 1-3期

关键词：

stochastic programming; decomposition; primal methods; dual methods; stochastic methods;

D O I：

10.1007/BF02614323

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

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. (C) 1997 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.

引用

页码：333 / 353

页数：21

共 42 条

[1]

[Anonymous], NUMERICAL TECHNIQUES

[2]

[Anonymous], 1983, STUDIES MATH ITS APP

[3]

[Anonymous], 1996, OPTIMIZATION STOCHAS

[4]

BENDERS JF, 1962, NUMER MATH, V4, P238, DOI [10.1007/BF01386316, DOI 10.1007/BF01386316, DOI 10.1007/S10287-004-0020-Y]