Stability, Approximation, and Decomposition in Two- and Multistage Stochastic Programming
Seiten
2009
Vieweg & Teubner (Verlag)
978-3-8348-0921-6 (ISBN)
Vieweg & Teubner (Verlag)
978-3-8348-0921-6 (ISBN)
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.
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.
Dr. Christian Küchler completed his doctoral thesis at the Humboldt University, Berlin. He currently works as a quantitative analyst at Landesbank Berlin AG.
Stability of Multistage Stochastic Programs.- Recombining Trees for Multistage Stochastic Programs.- Scenario Reduction with Respect to Discrepancy Distances.
| Erscheint lt. Verlag | 24.9.2009 |
|---|---|
| Reihe/Serie | Stochastic Programming |
| Zusatzinfo | 184 p. 49 illus. |
| Verlagsort | Wiesbaden |
| Sprache | englisch |
| Maße | 148 x 210 mm |
| Gewicht | 363 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Angewandte Mathematik |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| Schlagworte | algorithms • Konvergenzaussagen • Nested Benders Dekompositionsalgorithmus • Optimization • quantitative Stabilität • Reduktionsproblem • Stochastik • Stochastische Programmierung |
| ISBN-10 | 3-8348-0921-7 / 3834809217 |
| ISBN-13 | 978-3-8348-0921-6 / 9783834809216 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
Mehr entdecken
aus dem Bereich
aus dem Bereich
Buch | Softcover (2024)
Springer Vieweg (Verlag)
CHF 53,15
Buch | Softcover (2024)
Springer Vieweg (Verlag)
CHF 62,95
für Ingenieure und Naturwissenschaftler
Buch | Softcover (2024)
Springer Vieweg (Verlag)
CHF 48,95
