Stability, Approximation, and Decomposition in Two- and Multistage Stochastic Programming
Stochastic programming provides a framework for modelling, analyzing, and solving optimization problems with some parameters being not known up to a probability distribution. Such problems arise in a variety of applications, such as inventory control, financial planning and portfolio optimization, a...
Enregistré dans:
| Hovedforfatter: | |
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| Format: | Livre numérique |
| Sprog: | Anglais |
| Udgivet: |
Wiesbaden :
Vieweg+Teubner Verlag
[20..].
Cham : Springer Nature |
| Udgivelse: | 1st ed. 2009. |
| Serier: | Stochastic Programming
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| Online adgang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Kommentar: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Stability, Approximation, and Decomposition in Two- and Multistage Stochastic Programming, Texte imprimé, 9783834809216 |
| Summary: | Stochastic programming provides a framework for modelling, analyzing, and solving optimization problems with some parameters being not known up to a probability distribution. Such problems arise in a variety of applications, such as inventory control, financial planning and portfolio optimization, airline revenue management, scheduling and operation of power systems, and supply chain management. Christian Küchler studies various aspects of the stability of stochastic optimization problems as well as approximation and decomposition methods in stochastic programming. In particular, the author presents an extension of the Nested Benders decomposition algorithm related to the concept of recombining scenario trees. The approach combines the concept of cut sharing with a specific aggregation procedure and prevents an exponentially growing number of subproblem evaluations. Convergence results and numerical properties are discussed. |
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| Emne beskrivelse: | Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| ISBN: | 9783834893994 |
| ISSN: | 2945-8781 |
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