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Some advances in decomposition methodsfor stochastic linear programming

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  • Andrzej Ruszczynski

Abstract

Stochastic programming problems have very large dimension and characteristic structureswhich are tractable by decomposition. We review some new developments in cutting planemethods, augmented Lagrangian and splitting methods for linear multi‐stage stochasticprogramming problems. Copyright Kluwer Academic Publishers 1999

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  • Andrzej Ruszczynski, 1999. "Some advances in decomposition methodsfor stochastic linear programming," Annals of Operations Research, Springer, vol. 85(0), pages 153-172, January.
    • Handle: RePEc:spr:annopr:v:85:y:1999:i:0:p:153-172:10.1023/a:1018965626303
    DOI: 10.1023/A:1018965626303
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    Cited by:

    1. Schwarz, Hannes & Bertsch, Valentin & Fichtner, Wolf, 2015. "Two-stage stochastic, large-scale optimization of a decentralized energy system - a residential quarter as case study," Working Paper Series in Production and Energy 10, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    2. Hannes Schwarz & Valentin Bertsch & Wolf Fichtner, 2018. "Two-stage stochastic, large-scale optimization of a decentralized energy system: a case study focusing on solar PV, heat pumps and storage in a residential quarter," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 265-310, January.

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