Optimization Under Stochastic Uncertainty : Methods, Control and Random Search Methods

Lingua: inglese

Editore: Springer, 2020

3030556611 / 9783030556617

Serie: Libro 289 di 323 - International Series in Operations Research & Management Science

Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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Druck auf Anfrage Neuware - Printed after ordering - This book examines application and methods to incorporating stochastic parameter variations into the optimization process to decrease expense in corrective measures. Basic types of deterministic substitute problems occurring mostly in practice involve i) minimization of the expected primary costs subject to expected recourse cost constraints (reliability constraints) and remaining deterministic constraints, e.g. box constraints, as well as ii) minimization of the expected total costs (costs of construction, design, recourse costs, etc.) subject to the remaining deterministic constraints.After an introduction into the theory of dynamic control systems with random parameters, the major control laws are described, as open-loop control, closed-loop, feedback control and open-loop feedback control, used for iterative construction of feedback controls. For approximate solution of optimization and control problems with random parameters and involving expected cost/loss-type objective,constraint functions, Taylor expansion procedures, and Homotopy methods are considered, Examples and applications to stochastic optimization of regulators are given. Moreover, for reliability-based analysis and optimal design problems, corresponding optimization-based limit state functions are constructed. Because of the complexity of concrete optimization/control problems and their lack of the mathematical regularity as required of Mathematical Programming (MP) techniques, other optimization techniques, like random search methods (RSM) became increasingly important.Basic results on the convergence and convergence rates of random search methods are presented. Moreover, for the improvement of the - sometimes very low - convergence rate of RSM, search methods based on optimal stochastic decision processes are presented. In order to improve the convergence behavior of RSM, the random search procedure is embedded into a stochastic decision process for an optimal control ofthe probability distributions of the search variates (mutation random variables).

Codice articolo 9783030556617

Titolo
Optimization Under Stochastic Uncertainty : Methods, Control and Random Search Methods
Autore
Kurt Marti
Editore
Springer
Anno di pubblicazione
2020
Condizione
Neu
Rilegatura
Buch
Lingua
inglese
ISBN 10
3030556611
ISBN 13
9783030556617
Peso dell'articolo
776 grammi
Dimensioni
241x160x28 mm
Serie
Libro 289 di 323: International Series in Operations Research & Management Science

AHA-BUCH GmbH

Einbeck, Germania

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

Tariffe di spedizione da Germania a U.S.A.

ArticoloDa 5 a 7 giorni lavorativiDa 7 a 10 giorni lavorativi
Primo articoloEUR 30,50EUR 30,50
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