Optimization problems arising in practice involve random model parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insenistive with respect to random parameter variations, appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Several deterministic and stochastic approximation methods are provided: Taylor expansion methods, regression and response surface methods (RSM), probability inequalities, multiple linearization of survival/failure domains, discretization methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation and gradient procedures, differentiation formulas for probabilities and expectations.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Dr. Kurt Marti is a full Professor of Engineering Mathematics at the „Federal Armed Forces University of Munich“. He is Chairman of the IFIP-Working Group 7.7 on “Stochastic Optimization” and has been Chairman of the GAMM-Special Interest Group “Applied Stochastics and Optimization”. Professor Marti has published several books, both in German and in English, and he is author of more than 160 papers in refereed journals.
Optimization problems arising in practice involve random model parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Several deterministic and stochastic approximation methods are provided: Taylor expansion methods, regression and response surface methods (RSM), probability inequalities, multiple linearization of survival/failure domains, discretization methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation and gradient procedures, differentiation formulas for probabilities and expectations.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
EUR 28,91 für den Versand von Vereinigtes Königreich nach Deutschland
Versandziele, Kosten & DauerGratis für den Versand innerhalb von/der Deutschland
Versandziele, Kosten & DauerAnbieter: moluna, Greven, Deutschland
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Many illustrations/several examples/applications to concrete problems from engineering and operations research, as e.g. quality engineering, robust design/many references to stochastic optimization, stochastic programming and its application to engineeri. Bestandsnummer des Verkäufers 5048830
Anzahl: Mehr als 20 verfügbar
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. Neuware -Optimization problems arising in practice involve random model parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insenistive with respect to random parameter variations, appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Several deterministic and stochastic approximation methods are provided: Taylor expansion methods, regression and response surface methods (RSM), probability inequalities, multiple linearization of survival/failure domains, discretization methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation and gradient procedures, differentiation formulas for probabilities and expectations.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 356 pp. Englisch. Bestandsnummer des Verkäufers 9783642098369
Anzahl: 2 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Optimization problems arising in practice involve random model parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insenistive with respect to random parameter variations, appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Several deterministic and stochastic approximation methods are provided: Taylor expansion methods, regression and response surface methods (RSM), probability inequalities, multiple linearization of survival/failure domains, discretization methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation and gradient procedures, differentiation formulas for probabilities and expectations. Bestandsnummer des Verkäufers 9783642098369
Anzahl: 1 verfügbar
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Optimization problems arising in practice involve random model parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insenistive with respect to random parameter variations, appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Several deterministic and stochastic approximation methods are provided: Taylor expansion methods, regression and response surface methods (RSM), probability inequalities, multiple linearization of survival/failure domains, discretization methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation and gradient procedures, differentiation formulas for probabilities and expectations. 356 pp. Englisch. Bestandsnummer des Verkäufers 9783642098369
Anzahl: 2 verfügbar
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In. Bestandsnummer des Verkäufers ria9783642098369_new
Anzahl: Mehr als 20 verfügbar
Anbieter: Books Puddle, New York, NY, USA
Zustand: New. pp. 356 2nd Edition. Bestandsnummer des Verkäufers 263060219
Anzahl: 4 verfügbar
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. PRINT ON DEMAND pp. 356. Bestandsnummer des Verkäufers 183060209
Anzahl: 4 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Print on Demand pp. 356 23 Illus. Bestandsnummer des Verkäufers 5836324
Anzahl: 4 verfügbar
Anbieter: Mispah books, Redhill, SURRE, Vereinigtes Königreich
Paperback. Zustand: Like New. Like New. book. Bestandsnummer des Verkäufers ERICA77336420983636
Anzahl: 1 verfügbar
Anbieter: Lucky's Textbooks, Dallas, TX, USA
Zustand: New. Bestandsnummer des Verkäufers ABLIING23Mar3113020218098
Anzahl: Mehr als 20 verfügbar