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) |
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Research Programs: | Optimization under Uncertainty (OPT) |
Depositing User: | IIASA Import |
Date Deposited: | 15 Jan 2016 02:08 |
Last Modified: | 27 Aug 2021 17:15 |
URI: | https://pure.iiasa.ac.at/5011 |
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