A general algorithm for solving two-stage stochastic mixed 0–1 first-stage problems

We present an algorithmic approach for solving large-scale two-stage stochastic problems having mixed 0–1 first stage variables. The constraints in the first stage of the deterministic equivalent model have 0–1 variables and continuous variables, while the constraints in the second stage have only c...

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Veröffentlicht in:	Computers & operations research Jg. 36; H. 9; S. 2590 - 2600
Hauptverfasser:	Escudero, L.F., Garín, M.A., Merino, M., Pérez, G.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Kidlington Elsevier Ltd 01.09.2009 Elsevier Pergamon Press Inc
Schlagworte:	Algorithms Applied sciences Benders decomposition Branch-and-fix coordination Exact sciences and technology Integer programming Mathematical programming Nonanticipativity constraints Operational research and scientific management Operational research. Management science Problem solving Splitting variables Stochastic models Studies Twin node family Two-stage stochastic integer programming Twin node family Two-stage stochastic integer programming Branch-and-fix coordination Splitting variables Benders decomposition Nonanticipativity constraints Script Partition method Algorithmics Cluster Linear programming Stochastic programming Integer programming Zero one programming Deterministic model Mixed problem Large scale
ISSN:	0305-0548, 1873-765X, 0305-0548
Online-Zugang:	Volltext
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