On the Regularized Decomposition Method for Two Stage Stochastic Linear Problems

Ruszczynski A & Swietanowski A (1996). On the Regularized Decomposition Method for Two Stage Stochastic Linear Problems. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-96-014

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Abstract

A new approach to the regularized decomposition (RD) algorithm for two stage stochastic problems is presented. The RD method combines the ideas of the Dantzig-Wolfe decomposition principle and modern nonsmooth optimization methods. A new subproblem solution method using the primal simplex algorithm for linear programming is proposed and then tested on a number of large scale problems. The new approach makes it possible to use a more general problem formulation and thus allows considerably more freedom when creating the model. The computational results are highly encouraging.

Item Type: Monograph (IIASA Working Paper)
Research Programs: Optimization under Uncertainty (OPT)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:08
Last Modified: 24 Jul 2016 12:01
URI: http://pure.iiasa.ac.at/5011

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