Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 239, Issue 2, Pages 437-448Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ejor.2014.05.010
Keywords
Stochastic programming; Two-stage problems; Decomposition; Bundle methods
Funding
- Deutsche Forschungsgemeinschaft (DFG) [SU136/8-1]
- European Union
- European Social Fund through the National Research Center for the Development and Market Introduction of Advanced Information and Communication Technologies [TAMOP-4.2.2.C-11/1/KONV-2012-0004]
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Traditionally, two variants of the L-shaped method based on Benders' decomposition principle are used to solve two-stage stochastic programming problems: the aggregate and the disaggregate version. In this study we report our experiments with a special convex programming method applied to the aggregate master problem. The convex programming method is of the type that uses an oracle with on-demand accuracy. We use a special form which, when applied to two-stage stochastic programming problems, is shown to integrate the advantages of the traditional variants while avoiding their disadvantages. On a set of 105 test problems, we compare and analyze parallel implementations of regularized and unregularized versions of the algorithms. The results indicate that solution times are significantly shortened by applying the concept of on-demand accuracy. (C) 2014 Elsevier B.V. All rights reserved.
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