An exact algorithm for solving large-scale two-stage stochastic mixed-integer problems: Some theoretical and experimental aspects

We present an algorithmic framework, so-called BFC-TSMIP, for solving two-stage stochastic mixed 0–1 problems. The constraints in the Deterministic Equivalent Model have 0–1 variables and continuous variables at any stage. The approach uses the Twin Node Family ( TNF) concept within an adaptation of...

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Veröffentlicht in:European journal of operational research Jg. 204; H. 1; S. 105 - 116
Hauptverfasser: Escudero, L.F., Garín, M.A., Merino, M., Pérez, G.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 01.07.2010
Elsevier
Elsevier Sequoia S.A
Schriftenreihe:European Journal of Operational Research
Schlagworte:
ISSN:0377-2217, 1872-6860
Online-Zugang:Volltext
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Zusammenfassung:We present an algorithmic framework, so-called BFC-TSMIP, for solving two-stage stochastic mixed 0–1 problems. The constraints in the Deterministic Equivalent Model have 0–1 variables and continuous variables at any stage. The approach uses the Twin Node Family ( TNF) concept within an adaptation of the algorithmic framework so-called Branch-and-Fix Coordination for satisfying the nonanticipativity constraints for the first stage 0–1 variables. Jointly we solve the mixed 0–1 submodels defined at each TNF integer set for satisfying the nonanticipativity constraints for the first stage continuous variables. In these submodels the only integer variables are the second stage 0–1 variables. A numerical example and some theoretical and computational results are presented to show the performance of the proposed approach.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2009.09.027