Accelerating the regularized decomposition method for two stage stochastic linear problems

Andrzej Ruszczyński , Artur Świętanowski

Abstract

Practical improvements of the regularized decomposition algorithm for two stage stochastic problems are presented. They are associated with the primal simplex method for solving subproblems. A penalty formulation of the subproblems is used, which facilitates crash and warm starts, and allows more freedom when creating the model. The computational results are highly encouraging.
Author Andrzej Ruszczyński (FEIT / AK)
Andrzej Ruszczyński,,
- The Institute of Control and Computation Engineering
, Artur Świętanowski (FEIT / AK)
Artur Świętanowski,,
- The Institute of Control and Computation Engineering
Journal seriesEuropean Journal of Operational Research, ISSN 0377-2217
Issue year1997
Vol101
No2
Pages328-342
Keywords in EnglishDecomposition, Non-smooth optimization, Stochastic programming
DOIDOI:10.1016/S0377-2217(96)00401-8
URL http://www.sciencedirect.com/science/article/pii/S0377221796004018
Score (nominal)40
Publication indicators WoS Impact Factor: 2006 = 0.918 (2) - 2007=1.568 (5)
Citation count*93 (2015-04-30)
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