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

Handbook of simulation optimization

Fu, Michael C.

Linked to FindBook

Google Book

Amazon

博客來

Handbook of simulation optimization

Record Type:	Electronic resources : Monograph/item
Title/Author:	Handbook of simulation optimization/ edited by Michael C Fu.
other author:	Fu, Michael C.
Published:	New York, NY :Springer New York : : 2015.,
Description:	xvi, 387 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Overview of the Handbook -- Discrete Optimization via Simulation -- Ranking and Selection: Efficient Simulation Budget Allocation -- Response Surface Methodology -- Stochastic Gradient Estimation -- An Overview of Stochastic Approximation -- Stochastic Approximation Methods and Their Finite-time Convergence Properties -- A Guide to Sample Average Approximation -- Stochastic Constraints and Variance Reduction Techniques -- A Review of Random Search Methods -- Stochastic Adaptive Search Methods: Theory and Implementation -- Model-Based Stochastic Search Methods -- Solving Markov Decision Processes via Simulation.
Contained By:	Springer eBooks
Subject:	Simulation methods. -
Online resource:	http://dx.doi.org/10.1007/978-1-4939-1384-8
ISBN:	9781493913848 (electronic bk.)

Handbook of simulation optimization
Handbook of simulation optimization[electronic resource] /edited by Michael C Fu. - New York, NY :Springer New York :2015. - xvi, 387 p. :ill. (some col.), digital ;24 cm. - International series in operations research & management science,v.2160884-8289 ;. - International series in operations research & management science ;89..

Overview of the Handbook -- Discrete Optimization via Simulation -- Ranking and Selection: Efficient Simulation Budget Allocation -- Response Surface Methodology -- Stochastic Gradient Estimation -- An Overview of Stochastic Approximation -- Stochastic Approximation Methods and Their Finite-time Convergence Properties -- A Guide to Sample Average Approximation -- Stochastic Constraints and Variance Reduction Techniques -- A Review of Random Search Methods -- Stochastic Adaptive Search Methods: Theory and Implementation -- Model-Based Stochastic Search Methods -- Solving Markov Decision Processes via Simulation.

The Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology. Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods, and Markov decision processes. This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners, and graduate students in the business/engineering fields of operations research, management science, operations management, and stochastic control, as well as in economics/finance and computer science.

ISBN: 9781493913848 (electronic bk.)

Standard No.: 10.1007/978-1-4939-1384-8doiSubjects--Topical Terms:

581321
Simulation methods.

LC Class. No.: T57.62 / .H36 2015

Dewey Class. No.: 003.76

Handbook of simulation optimization
LDR:02820nmm a2200337 a 4500 001 1993374
003 DE-He213
005 20150630134654.0
006 m d
007 cr nn 008maaau
008 151019s2015 nyu s 0 eng d
020 $a 9781493913848 (electronic bk.)
020 $a 9781493913831 (paper)
024 7 $a 10.1007/978-1-4939-1384-8 $2 doi
035 $a 978-1-4939-1384-8
040 $a GP $c GP
041 0 $a eng
050 4 $a T57.62 $b .H36 2015
072 7 $a KJT $2 bicssc
072 7 $a KJMD $2 bicssc
072 7 $a BUS049000 $2 bisacsh
082 0 4 $a 003.76 $2 23
090 $a T57.62 $b .H236 2015
245 0 0 $a Handbook of simulation optimization $h [electronic resource] / $c edited by Michael C Fu.
260 $a New York, NY : $b Springer New York : $b Imprint: Springer, $c 2015.
300 $a xvi, 387 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a International series in operations research & management science, $x 0884-8289 ; $v v.216
505 0 $a Overview of the Handbook -- Discrete Optimization via Simulation -- Ranking and Selection: Efficient Simulation Budget Allocation -- Response Surface Methodology -- Stochastic Gradient Estimation -- An Overview of Stochastic Approximation -- Stochastic Approximation Methods and Their Finite-time Convergence Properties -- A Guide to Sample Average Approximation -- Stochastic Constraints and Variance Reduction Techniques -- A Review of Random Search Methods -- Stochastic Adaptive Search Methods: Theory and Implementation -- Model-Based Stochastic Search Methods -- Solving Markov Decision Processes via Simulation.
520 $a The Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology. Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods, and Markov decision processes. This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners, and graduate students in the business/engineering fields of operations research, management science, operations management, and stochastic control, as well as in economics/finance and computer science.
650 0 $a Simulation methods. $3 581321
650 0 $a Mathematical optimization. $3 517763
650 0 $a Stochastic processes. $3 520663
650 0 $a Operations research. $3 547123
650 1 4 $a Economics/Management Science. $3 890844
650 2 4 $a Operation Research/Decision Theory. $3 1620900
650 2 4 $a Simulation and Modeling. $3 890873
650 2 4 $a Operations Research, Management Science. $3 1532996
650 2 4 $a Game Theory/Mathematical Methods. $3 892394
700 1 $a Fu, Michael C. $3 848584
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a International series in operations research & management science ; $v 89. $3 1305920
856 4 0 $u http://dx.doi.org/10.1007/978-1-4939-1384-8
950 $a Business and Economics (Springer-11643)