全球智库信息集成服务系统(G2TT): A Lagrangian Finite Generation Technique for Solving Linear-Quadratic Problems in Stochastic Programming.

G2TT

来源类型	Monograph (IIASA Working Paper)
规范类型	论文
	A Lagrangian Finite Generation Technique for Solving Linear-Quadratic Problems in Stochastic Programming.
	Rockafellar RT; Wets RJ-B
发表日期	1984
出版者	IIASA, Laxenburg, Austria: WP-84-025
出版年	1984
语种	英语
摘要	A new method is proposed for solving two-stage problems in linear and quadratic stochastic programming. Such problems are dualized, and the dual, although itself of high dimension, is approximated by a sequence of quadratic programming subproblems whose dimensionality can be kept low. These subproblems correspond to maximizing the dual objective over the convex hull of finitely many dual feasible solutions. An optimizing sequence is produced for the primal problem that converges at a linear rate in the strongly quadratic case. An outer algorithm of augmented Lagrangian type can be used to introduce strongly quadratic terms, if desired.
主题	Adaption and Optimization (ADO)
URL	http://pure.iiasa.ac.at/id/eprint/2493/
来源智库	International Institute for Applied Systems Analysis (Austria)
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/123058
推荐引用方式 GB/T 7714	Rockafellar RT,Wets RJ-B. A Lagrangian Finite Generation Technique for Solving Linear-Quadratic Problems in Stochastic Programming.. 1984.