Decomposition methods in stochastic programming |
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Authors: | Andrzej Ruszczyński |
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Affiliation: | (1) Department of Industrial Engineering, University of Wisconsin-Madison, 1513 University Avenue, 53706 Madison, WI, USA;(2) Present address: Department of Electronics and Computer Science, Warsaw University of Technology, Poland |
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Abstract: | Stochastic programming problems have very large dimension and characteristic structures which are tractable by decomposition. We review basic ideas of cutting plane methods, augmented Lagrangian and splitting methods, and stochastic decomposition methods for convex polyhedral multi-stage stochastic programming problems. |
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Keywords: | Stochastic programming Decomposition Primal methods Dual methods Stochastic methods |
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