000			02687nmm a22002895i 4500
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008			100301s2008 gw | s |||| 0|eng d
020			_a9783540794585 _9978-3-540-79458-5
082			_a658.403 _223
100			_aMarti, Kurt. _921123
245			_aStochastic Optimization Methods _h[electronic resource] / _cby Kurt Marti.
250			_a2nd ed. 2008.
260			_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2008.
300			_aXIII, 340 p. _bonline resource.
505			_aBasic Stochastic Optimization Methods -- Decision/Control Under Stochastic Uncertainty -- Deterministic Substitute Problems in Optimal Decision Under Stochastic Uncertainty -- Differentiation Methods -- Differentiation Methods for Probability and Risk Functions -- Deterministic Descent Directions -- Deterministic Descent Directions and Efficient Points -- Semi-Stochastic Approximation Methods -- RSM-Based Stochastic Gradient Procedures -- Stochastic Approximation Methods with Changing Error Variances -- Reliability Analysis of Structures/Systems -- Computation of Probabilities of Survival/Failure by Means of Piecewise Linearization of the State Function.
520			_aOptimization 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.
650			_aOperations research. _921124
650			_aMathematical optimization. _921125
650			_aEngineering. _921126
650			_aComputational intelligence. _921127
650			_aOperations Research and Decision Theory. _921128
650			_aOptimization. _921129
650			_aTechnology and Engineering. _921130
650			_aComputational Intelligence. _921131
856			_uhttps://doi.org/10.1007/978-3-540-79458-5
942			_cEBK
999			_c13720 _d13720