Stochastic optimization methods : applications in engineering and operations research /

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Bibliographic Details
Author / Creator:Marti, Kurt, 1943- author.
Edition:Third edition.
Imprint:Heidelberg : Springer, 2015.
Description:1 online resource (xxiv, 368 pages) : illustrations
Language:English
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11092040
Hidden Bibliographic Details
ISBN:9783662462140
3662462141
3662462133
9783662462133
9783662462133
Notes:Includes bibliographical references and index.
Online resource; title from PDF title page (SpringerLink, viewed February 25, 2015).
Summary:This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, i.e., optimal solutions that are insensitive with respect to random parameter variations, where 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 probabilities and expectations involved, the book also shows how to apply approximative solution techniques. 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, and differentiation formulas for probabilities and expectations. In the third edition, this book further develops stochastic optimization methods. In particular, it now shows how to apply stochastic optimization methods to the approximate solution of important concrete problems arising in engineering, economics and operations research.
Other form:Printed edition: 9783662462133
Standard no.:10.1007/978-3-662-46214-0

MARC

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100 1 |a Marti, Kurt,  |d 1943-  |e author.  |0 http://id.loc.gov/authorities/names/n79080115  |1 http://viaf.org/viaf/109477250 
245 1 0 |a Stochastic optimization methods :  |b applications in engineering and operations research /  |c Kurt Marti. 
250 |a Third edition. 
264 1 |a Heidelberg :  |b Springer,  |c 2015. 
300 |a 1 online resource (xxiv, 368 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent  |0 http://id.loc.gov/vocabulary/contentTypes/txt 
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504 |a Includes bibliographical references and index. 
588 0 |a Online resource; title from PDF title page (SpringerLink, viewed February 25, 2015). 
520 |a This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, i.e., optimal solutions that are insensitive with respect to random parameter variations, where 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 probabilities and expectations involved, the book also shows how to apply approximative solution techniques. 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, and differentiation formulas for probabilities and expectations. In the third edition, this book further develops stochastic optimization methods. In particular, it now shows how to apply stochastic optimization methods to the approximate solution of important concrete problems arising in engineering, economics and operations research. 
505 0 |a Stochastic Optimization Methods -- Optimal Control Under Stochastic Uncertainty -- Stochastic Optimal Open-Loop Feedback Control -- Adaptive Optimal Stochastic Trajectory Planning and Control (AOSTPC) -- Optimal Design of Regulators -- Expected Total Cost Minimum Design of Plane Frames -- Stochastic Structural Optimization with Quadratic Loss Functions -- Maximum Entropy Techniques. 
650 0 |a Stochastic processes.  |0 http://id.loc.gov/authorities/subjects/sh85128181 
650 0 |a Mathematical optimization.  |0 http://id.loc.gov/authorities/subjects/sh85082127 
650 7 |a MATHEMATICS  |x Applied.  |2 bisacsh 
650 7 |a MATHEMATICS  |x Probability & Statistics  |x General.  |2 bisacsh 
650 7 |a Mathematical optimization.  |2 fast  |0 (OCoLC)fst01012099 
650 7 |a Stochastic processes.  |2 fast  |0 (OCoLC)fst01133519 
655 4 |a Electronic books. 
776 0 8 |i Printed edition:  |z 9783662462133 
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928 |t Library of Congress classification  |a QA274 .M37 2015eb  |l Online  |c UC-FullText  |u http://link.springer.com/10.1007/978-3-662-46214-0  |z SpringerLink  |g ebooks  |i 9905660