On BFC-MSMIP strategies for scenario cluster partitioning, and twin node family branching selection and bounding for multistage stochastic mixed integer programming

In the branch-and-fix coordination ( BFC-MSMIP) algorithm for solving large-scale multistage stochastic mixed integer programming problems, we find it crucial to decide the stages where the nonanticipativity constraints are explicitly considered in the model. This information is materialized when th...

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Veröffentlicht in:Computers & operations research Jg. 37; H. 4; S. 738 - 753
Hauptverfasser: Escudero, Laureano F., Araceli Garín, María, Merino, María, Pérez, Gloria
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Kidlington Elsevier Ltd 01.04.2010
Elsevier
Pergamon Press Inc
Schlagworte:
Algorithms
Applied sciences
Branch & bound algorithms
Branch-and-fix coordination
Cluster analysis
Clusters
Efficiency
Exact sciences and technology
Integer programming
Mathematical programming
Mixed integer
Multistage
Multistage stochastic mixed 0–1 programming
Nonanticipativity constraints
Operational research and scientific management
Operational research. Management science
Operations research
Programming
Scenario cluster partitioning
Stochastic models
Stochasticity
Strategy
Studies
Twin node family
Twin node family
Multistage stochastic mixed 0–1 programming
Branch-and-fix coordination
Scenario cluster partitioning
Nonanticipativity constraints
Branching
Partition
Script
Mixed programming
Cluster
Mixed integer programming
Modeling
Stochastic programming
Zero one programming
Partitioning
Multistage stochastic mixed 0-1 programming
Large scale
ISSN:0305-0548, 1873-765X, 0305-0548
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Zusammenfassung:In the branch-and-fix coordination ( BFC-MSMIP) algorithm for solving large-scale multistage stochastic mixed integer programming problems, we find it crucial to decide the stages where the nonanticipativity constraints are explicitly considered in the model. This information is materialized when the full model is broken down into a scenario cluster partition with smaller subproblems. In this paper we present a scheme for obtaining strong bounds and branching strategies for the Twin Node Families to increase the efficiency of the procedure BFC-MSMIP, based on the information provided by the nonanticipativity constraints that are explicitly considered in the problem. Some computational experience is reported to support the efficiency of the new scheme.
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ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2009.06.023