Abstract
Stochastic programs are proper tools for real-time optimization if real-time features arise due to lack of data information at the moment of decision. The paper’s focus is at two-stage linear stochastic programs involving integer requirements. After a discussion of basic structural properties, two decomposition approaches are developed. While the first approach is directed to decomposition of the stochastic program itself, the second deals with decomposition of the related Graver test set.
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Hemmecke, R., Schultz, R. (2001). Decomposition Methods for Two-Stage Stochastic Integer Programs. In: Grötschel, M., Krumke, S.O., Rambau, J. (eds) Online Optimization of Large Scale Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04331-8_30
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DOI: https://doi.org/10.1007/978-3-662-04331-8_30
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