A Scenario Tree-Based Decomposition for Solving Multistage Stochastic Programs [recurso electrónico] : With Application in Energy Production / by Debora Mahlke.
Tipo de material:
TextoEditor: Wiesbaden : Vieweg+Teubner, 2011Descripción: XVI, 182p. 14 illus. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783834898296Tema(s): Mathematics | Mathematics | Applications of MathematicsFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 519 Clasificación LoC:T57-57.97Recursos en línea: Libro electrónico
En: Springer eBooksResumen: Optimization problems involving uncertain data arise in many areas of industrial and economic applications. Stochastic programming provides a useful framework for modeling and solving optimization problems for which a probability distribution of the unknown parameters is available. Motivated by practical optimization problems occurring in energy systems with regenerative energy supply, Debora Mahlke formulates and analyzes multistage stochastic mixed-integer models. For their solution, the author proposes a novel decomposition approach which relies on the concept of splitting the underlying scenario tree into subtrees. Based on the formulated models from energy production, the algorithm is computationally investigated and the numerical results are discussed.
| Tipo de ítem | Biblioteca actual | Colección | Signatura | Copia número | Estado | Fecha de vencimiento | Código de barras |
|---|---|---|---|---|---|---|---|
| Libro Electrónico | Biblioteca Electrónica | Colección de Libros Electrónicos | T57 -57.97 (Browse shelf(Abre debajo)) | 1 | No para préstamo | 377104-2001 |
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| T57 -57.97 Asymptotic Stability of Steady Compressible Fluids | T57 -57.97 Damped Oscillations of Linear Systems | T57 -57.97 Front Tracking for Hyperbolic Conservation Laws | T57 -57.97 A Scenario Tree-Based Decomposition for Solving Multistage Stochastic Programs | T57 -57.97 Teoria Spettrale e Meccanica Quantistica | T57 -57.97 Calcul Scientifique | T57 -57.97 Un mondo di idee |
Optimization problems involving uncertain data arise in many areas of industrial and economic applications. Stochastic programming provides a useful framework for modeling and solving optimization problems for which a probability distribution of the unknown parameters is available. Motivated by practical optimization problems occurring in energy systems with regenerative energy supply, Debora Mahlke formulates and analyzes multistage stochastic mixed-integer models. For their solution, the author proposes a novel decomposition approach which relies on the concept of splitting the underlying scenario tree into subtrees. Based on the formulated models from energy production, the algorithm is computationally investigated and the numerical results are discussed.
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