Stochastic Optimization Methods
Marti, Kurt
Stochastic Optimization Methods [electronic resource] - 2nd ed. - New York : Springer June 2008
License restrictions may limit access.
Annotation 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.
College Audience Springer
9783540794578 3540794573 (Trade Cloth) USD 139.00 Retail Price (Publisher) = Stochastic Optimization Methods
9783540794578
3540794573 00024965
QA402.S
519.62
Stochastic Optimization Methods [electronic resource] - 2nd ed. - New York : Springer June 2008
License restrictions may limit access.
Annotation 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.
College Audience Springer
9783540794578 3540794573 (Trade Cloth) USD 139.00 Retail Price (Publisher) = Stochastic Optimization Methods
9783540794578
3540794573 00024965
QA402.S
519.62