東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Stochastic optimization methods = ap...

Marti, Kurt.

Linked to FindBook

Google Book

Amazon

博客來

Stochastic optimization methods = applications in engineering and operations research /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Stochastic optimization methods/ by Kurt Marti.
Reminder of title:	applications in engineering and operations research /
Author:	Marti, Kurt.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2015.,
Description:	xxiv, 368 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Stochastic processes. -
Online resource:	http://dx.doi.org/10.1007/978-3-662-46214-0
ISBN:	9783662462140 (electronic bk.)

Stochastic optimization methods = applications in engineering and operations research /
Marti, Kurt.

Stochastic optimization methodsapplications in engineering and operations research /[electronic resource] :by Kurt Marti. - 3rd ed. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - xxiv, 368 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9783662462140 (electronic bk.)

Standard No.: 10.1007/978-3-662-46214-0doiSubjects--Topical Terms:

520663
Stochastic processes.

LC Class. No.: QA274

Dewey Class. No.: 519.23

Stochastic optimization methods = applications in engineering and operations research /
LDR:02750nmm a2200337 a 4500 001 1995176
003 DE-He213
005 20150914161708.0
006 m d
007 cr nn 008maaau
008 151019s2015 gw s 0 eng d
020 $a 9783662462140 (electronic bk.)
020 $a 9783662462133 (paper)
024 7 $a 10.1007/978-3-662-46214-0 $2 doi
035 $a 978-3-662-46214-0
040 $a GP $c GP
041 0 $a eng
050 4 $a QA274
072 7 $a KJT $2 bicssc
072 7 $a KJMD $2 bicssc
072 7 $a BUS049000 $2 bisacsh
082 0 4 $a 519.23 $2 23
090 $a QA274 $b .M378 2015
100 1 $a Marti, Kurt. $3 895707
245 1 0 $a Stochastic optimization methods $h [electronic resource] : $b applications in engineering and operations research / $c by Kurt Marti.
250 $a 3rd ed.
260 $a Berlin, Heidelberg : $b Springer Berlin Heidelberg : $b Imprint: Springer, $c 2015.
300 $a xxiv, 368 p. : $b ill., digital ; $c 24 cm.
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.
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.
650 0 $a Stochastic processes. $3 520663
650 0 $a Mathematical optimization. $3 517763
650 1 4 $a Economics/Management Science. $3 890844
650 2 4 $a Operation Research/Decision Theory. $3 1620900
650 2 4 $a Optimization. $3 891104
650 2 4 $a Computational Intelligence. $3 1001631
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-3-662-46214-0
950 $a Business and Economics (Springer-11643)