Handbook of Simulation Optimization

. Ed(s): Fu, Michael C.

ISBN 10: 1493951661 ISBN 13: 9781493951666
Editore: Springer-Verlag New York Inc., 2016
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Editor(s): Fu, Michael C. Series: International Series in Operations Research & Management Science. Num Pages: 403 pages, 9 black & white illustrations, 9 colour illustrations, 7 black & white tables, biography. BIC Classification: UYM. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 21. Weight in Grams: 617. . 2016. Softcover reprint of the original 1st ed. 2015. Paperback. . . . . Books ship from the US and Ireland. Codice articolo V9781493951666

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Riassunto:

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.

Informazioni sull?autore:

Dr. Michael C. Fu received his Ph.D. in applied mathematics from Harvard University and master's and bachelor's degrees in EECS and mathematics from MIT. Since 1989, he has been at the University of Maryland in the Robert H. Smith School of Business, where he is currently Ralph J. Tyser Professor of Management Science, with a joint appointment in the Institute for Systems Research (ISR) and an affiliate appointment in the Electrical and Computer Engineering Department, A. James Clark School of Engineering. At the University of Maryland, he was named a Distinguished Scholar-Teacher and received the ISR’s Outstanding Systems Engineering Faculty Award and the Business School's Allen J. Krowe Award for Teaching Excellence. He served as the Stochastic Models and Simulation Department Editor of Management Science from 2006-2008, as Simulation Area Editor of Operations Research from 2000-2005 and on the Editorial Boards of the INFORMS Journal on Computing, Mathematics of Operations Research, Production and Operations Management and IIE Transactions. He served as Program Chair of the 2011 Winter Simulation Conference and as Operations Research Program Director at the National Science Foundation from 2010-2012. His co-authored book, Conditional Monte Carlo: Gradient Estimation and Optimization Applications received the INFORMS College on Simulation Outstanding Publication Award. He also co-authored the research monograph Simulation-based Algorithms for Markov Decision Processes and co-edited the books Perspectives in Operations Research, Advances in Mathematical Finance and the 3rd edition of the Encyclopedia of Operations Research and Management Science. He is a Fellow of IEEE and the Institute of Operations Research and the Management Sciences (INFORMS).

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Titolo: Handbook of Simulation Optimization
Casa editrice: Springer-Verlag New York Inc.
Data di pubblicazione: 2016
Legatura: Brossura
Condizione: New

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Fu, Michael C.
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The first handbook on simulation optimizationOne of the hottest research topics and professionally-applied areas in OREditor is one of the most prominent names in the fieldDr. Michael C. Fu received his Ph.D. in applied mathemati. Codice articolo 447956273

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Taschenbuch. Condizione: Neu. Handbook of Simulation Optimization | Michael C Fu | Taschenbuch | xvi | Englisch | 2016 | Springer | EAN 9781493951666 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Codice articolo 103504000

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Taschenbuch. Condizione: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 404 pp. Englisch. Codice articolo 9781493951666

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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 404 pp. Englisch. Codice articolo 9781493951666

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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Codice articolo 9781493951666

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