Stochastic simulation optimization for discrete event systems: perturbation analysis, ordinal optimization, and beyond
Gespeichert in:
| Format: | Elektronisch E-Book |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
[Hackensack] New Jersey
World Scientific
2013
|
| Schlagworte: | |
| Online-Zugang: | FAW01 FAW02 Volltext |
| Beschreibung: | "Discrete event systems (DES) have become pervasive in our daily life. Examples include (but are not restricted to) manufacturing and supply chains, transportation, healthcare, call centers, and financial engineering. However, due to their complexities that often involve millions or even billions of events with many variables and constraints, modeling of these stochastic simulations has long been a "hard nut to crack". The advance in available computer technology, especially of cluster and cloud computing, has paved the way for the realization of a number of stochastic simulation optimization for complex discrete event systems. This book will introduce two important techniques initially proposed and developed by Professor Y.C. Ho and his team; namely perturbation analysis and ordinal optimization for stochastic simulation optimization, and present the state-of-the-art technology, and their future research directions. Contents: Part I: Perturbation Analysis: IPA Calculus for Hybrid Systems; Smoothed Perturbation Analysis: A Retrospective and Prospective Look; Perturbation Analysis and Variance Reduction in Monte Carlo Simulation; Adjoints and Averaging; Infinitesimal Perturbation Analysis in On-Line Optimization; Simulation-based Optimization of Failure-Prone Continuous Flow Lines; Perturbation Analysis, Dynamic Programming, and Beyond; Part II: Ordinal Optimization : Fundamentals of Ordinal Optimization; Optimal Computing Budget Allocation; Nested Partitions; Applications of Ordinal Optimization. Readership: Professionals in industrial and systems engineering, graduate reference for probability & statistics, stochastic analysis and general computer science, and research."-- Includes bibliographical references Chapter 1. The IPA calculus for hybrid systems -- chapter 2. Smoothed perturbation analysis : a retrospective and prospective look -- chapter 3. Perturbation analysis and variance reduction in Monte Carlo simulation -- chapter 4. Adjoints and averaging -- chapter 5. Infinitesimal perturbation analysis and optimization algorithms -- chapter 6. Simulation-based optimization of failure-prone continuous flow lines -- chapter 7. Perturbation analysis, dynamic programming, and beyond -- chapter 8. Fundamentals of ordinal optimization -- chapter 9. Optimal computing budget allocation framework -- chapter 10. Nested partitions -- chapter 11. Applications of ordinal optimization |
| Beschreibung: | 1 Online-Ressource (pages cm) |
| ISBN: | 9789814513005 9789814513012 9814513008 9814513016 |
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| 500 | |a "Discrete event systems (DES) have become pervasive in our daily life. Examples include (but are not restricted to) manufacturing and supply chains, transportation, healthcare, call centers, and financial engineering. However, due to their complexities that often involve millions or even billions of events with many variables and constraints, modeling of these stochastic simulations has long been a "hard nut to crack". The advance in available computer technology, especially of cluster and cloud computing, has paved the way for the realization of a number of stochastic simulation optimization for complex discrete event systems. This book will introduce two important techniques initially proposed and developed by Professor Y.C. Ho and his team; namely perturbation analysis and ordinal optimization for stochastic simulation optimization, and present the state-of-the-art technology, and their future research directions. Contents: Part I: Perturbation Analysis: IPA Calculus for Hybrid Systems; Smoothed Perturbation Analysis: A Retrospective and Prospective Look; Perturbation Analysis and Variance Reduction in Monte Carlo Simulation; Adjoints and Averaging; Infinitesimal Perturbation Analysis in On-Line Optimization; Simulation-based Optimization of Failure-Prone Continuous Flow Lines; Perturbation Analysis, Dynamic Programming, and Beyond; Part II: Ordinal Optimization : Fundamentals of Ordinal Optimization; Optimal Computing Budget Allocation; Nested Partitions; Applications of Ordinal Optimization. Readership: Professionals in industrial and systems engineering, graduate reference for probability & statistics, stochastic analysis and general computer science, and research."-- | ||
| 500 | |a Includes bibliographical references | ||
| 500 | |a Chapter 1. The IPA calculus for hybrid systems -- chapter 2. Smoothed perturbation analysis : a retrospective and prospective look -- chapter 3. Perturbation analysis and variance reduction in Monte Carlo simulation -- chapter 4. Adjoints and averaging -- chapter 5. Infinitesimal perturbation analysis and optimization algorithms -- chapter 6. Simulation-based optimization of failure-prone continuous flow lines -- chapter 7. Perturbation analysis, dynamic programming, and beyond -- chapter 8. Fundamentals of ordinal optimization -- chapter 9. Optimal computing budget allocation framework -- chapter 10. Nested partitions -- chapter 11. Applications of ordinal optimization | ||
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| id | DE-604.BV043162416 |
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| indexdate | 2024-07-10T07:19:24Z |
| institution | BVB |
| isbn | 9789814513005 9789814513012 9814513008 9814513016 |
| language | English |
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| owner | DE-1046 DE-1047 |
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| physical | 1 Online-Ressource (pages cm) |
| psigel | ZDB-4-EBA ZDB-4-EBA FAW_PDA_EBA |
| publishDate | 2013 |
| publishDateSearch | 2013 |
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| publisher | World Scientific |
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| spelling | Stochastic simulation optimization for discrete event systems perturbation analysis, ordinal optimization, and beyond edited by Chun-Hung Chen (George Mason University, USA), Qing-Shan Jia (Tsinghua University, China) & Loo Hay Lee (National University of Singapore, Singapore) [Hackensack] New Jersey World Scientific 2013 1 Online-Ressource (pages cm) txt rdacontent c rdamedia cr rdacarrier "Discrete event systems (DES) have become pervasive in our daily life. Examples include (but are not restricted to) manufacturing and supply chains, transportation, healthcare, call centers, and financial engineering. However, due to their complexities that often involve millions or even billions of events with many variables and constraints, modeling of these stochastic simulations has long been a "hard nut to crack". The advance in available computer technology, especially of cluster and cloud computing, has paved the way for the realization of a number of stochastic simulation optimization for complex discrete event systems. This book will introduce two important techniques initially proposed and developed by Professor Y.C. Ho and his team; namely perturbation analysis and ordinal optimization for stochastic simulation optimization, and present the state-of-the-art technology, and their future research directions. Contents: Part I: Perturbation Analysis: IPA Calculus for Hybrid Systems; Smoothed Perturbation Analysis: A Retrospective and Prospective Look; Perturbation Analysis and Variance Reduction in Monte Carlo Simulation; Adjoints and Averaging; Infinitesimal Perturbation Analysis in On-Line Optimization; Simulation-based Optimization of Failure-Prone Continuous Flow Lines; Perturbation Analysis, Dynamic Programming, and Beyond; Part II: Ordinal Optimization : Fundamentals of Ordinal Optimization; Optimal Computing Budget Allocation; Nested Partitions; Applications of Ordinal Optimization. Readership: Professionals in industrial and systems engineering, graduate reference for probability & statistics, stochastic analysis and general computer science, and research."-- Includes bibliographical references Chapter 1. The IPA calculus for hybrid systems -- chapter 2. Smoothed perturbation analysis : a retrospective and prospective look -- chapter 3. Perturbation analysis and variance reduction in Monte Carlo simulation -- chapter 4. Adjoints and averaging -- chapter 5. Infinitesimal perturbation analysis and optimization algorithms -- chapter 6. Simulation-based optimization of failure-prone continuous flow lines -- chapter 7. Perturbation analysis, dynamic programming, and beyond -- chapter 8. Fundamentals of ordinal optimization -- chapter 9. Optimal computing budget allocation framework -- chapter 10. Nested partitions -- chapter 11. Applications of ordinal optimization SCIENCE / System Theory bisacsh TECHNOLOGY & ENGINEERING / Operations Research bisacsh Mathematisches Modell Discrete-time systems Mathematical models Perturbation (Mathematics) Systems engineering Computer simulaton Stochastischer Prozess (DE-588)4057630-9 gnd rswk-swf Diskretes Ereignissystem (DE-588)4196828-1 gnd rswk-swf Simulation (DE-588)4055072-2 gnd rswk-swf Stochastischer Prozess (DE-588)4057630-9 s Simulation (DE-588)4055072-2 s Diskretes Ereignissystem (DE-588)4196828-1 s 1\p DE-604 Chen, Chun-Hung Sonstige oth Jia, Qing-Shan Sonstige oth Lee, Loo Hay Sonstige oth http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=605588 Aggregator Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Stochastic simulation optimization for discrete event systems perturbation analysis, ordinal optimization, and beyond SCIENCE / System Theory bisacsh TECHNOLOGY & ENGINEERING / Operations Research bisacsh Mathematisches Modell Discrete-time systems Mathematical models Perturbation (Mathematics) Systems engineering Computer simulaton Stochastischer Prozess (DE-588)4057630-9 gnd Diskretes Ereignissystem (DE-588)4196828-1 gnd Simulation (DE-588)4055072-2 gnd |
| subject_GND | (DE-588)4057630-9 (DE-588)4196828-1 (DE-588)4055072-2 |
| title | Stochastic simulation optimization for discrete event systems perturbation analysis, ordinal optimization, and beyond |
| title_auth | Stochastic simulation optimization for discrete event systems perturbation analysis, ordinal optimization, and beyond |
| title_exact_search | Stochastic simulation optimization for discrete event systems perturbation analysis, ordinal optimization, and beyond |
| title_full | Stochastic simulation optimization for discrete event systems perturbation analysis, ordinal optimization, and beyond edited by Chun-Hung Chen (George Mason University, USA), Qing-Shan Jia (Tsinghua University, China) & Loo Hay Lee (National University of Singapore, Singapore) |
| title_fullStr | Stochastic simulation optimization for discrete event systems perturbation analysis, ordinal optimization, and beyond edited by Chun-Hung Chen (George Mason University, USA), Qing-Shan Jia (Tsinghua University, China) & Loo Hay Lee (National University of Singapore, Singapore) |
| title_full_unstemmed | Stochastic simulation optimization for discrete event systems perturbation analysis, ordinal optimization, and beyond edited by Chun-Hung Chen (George Mason University, USA), Qing-Shan Jia (Tsinghua University, China) & Loo Hay Lee (National University of Singapore, Singapore) |
| title_short | Stochastic simulation optimization for discrete event systems |
| title_sort | stochastic simulation optimization for discrete event systems perturbation analysis ordinal optimization and beyond |
| title_sub | perturbation analysis, ordinal optimization, and beyond |
| topic | SCIENCE / System Theory bisacsh TECHNOLOGY & ENGINEERING / Operations Research bisacsh Mathematisches Modell Discrete-time systems Mathematical models Perturbation (Mathematics) Systems engineering Computer simulaton Stochastischer Prozess (DE-588)4057630-9 gnd Diskretes Ereignissystem (DE-588)4196828-1 gnd Simulation (DE-588)4055072-2 gnd |
| topic_facet | SCIENCE / System Theory TECHNOLOGY & ENGINEERING / Operations Research Mathematisches Modell Discrete-time systems Mathematical models Perturbation (Mathematics) Systems engineering Computer simulaton Stochastischer Prozess Diskretes Ereignissystem Simulation |
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| work_keys_str_mv | AT chenchunhung stochasticsimulationoptimizationfordiscreteeventsystemsperturbationanalysisordinaloptimizationandbeyond AT jiaqingshan stochasticsimulationoptimizationfordiscreteeventsystemsperturbationanalysisordinaloptimizationandbeyond AT leeloohay stochasticsimulationoptimizationfordiscreteeventsystemsperturbationanalysisordinaloptimizationandbeyond |