img Leseprobe Leseprobe

Stochastic Optimization Methods

Kurt Marti

PDF
ca. 117,69

Springer Berlin img Link Publisher

Sozialwissenschaften, Recht, Wirtschaft / Allgemeines, Lexika

Beschreibung

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.

Weitere Titel in dieser Kategorie
Cover What Next?
Jane Moffett
Cover The Valerian Ledger
Jonathan Hughes
Cover My Head For A Tree
Martin Goodman
Cover Retire Rich, Live Free
Thomas L. Danforth
Cover The Psychology of Money
Marcus P. Lancaster
Cover Breaking Money Silence
Kathleen Burns Kingsbury
Cover Gen Z Money
Jackson A. Cooper

Kundenbewertungen

Schlagwörter

Optimization Methods, Regression, model, Operations Research, calculus, Response Surface Methodology, Stochastic Optimization, Stochastic Approximation, Optimization, Optimization Problems