£90.05

Springer Stochastic Optimization Methods

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£108.00 £83.72 £89.02 £94.32 £99.61 £104.91 £110.21 09 June 2024 15 November 2024 24 April 2025 30 September 2025 09 March 2026

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Description

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.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
06 November 2010
Listed Since
12 September 2010

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