Design and Analysis of Simulation Experiments (International Series in Operations Research & Management Science Book 111) - Info and Reading Options
By Jack P. C. Kleijnen

"Design and Analysis of Simulation Experiments (International Series in Operations Research & Management Science Book 111)" was published by Springer in Nov 15, 2007 - United States - New York, NY, it has 220 pages and the language of the book is English.
“Design and Analysis of Simulation Experiments (International Series in Operations Research & Management Science Book 111)” Metadata:
- Title: ➤ Design and Analysis of Simulation Experiments (International Series in Operations Research & Management Science Book 111)
- Author: Jack P. C. Kleijnen
- Language: English
- Number of Pages: 220
- Publisher: Springer
- Publish Date: Nov 15, 2007
- Publish Location: United States - New York, NY
- Dewey Decimal Classification: 003
- Library of Congress Classification: QA273.A1-274.9T57.62 .K54 2008
“Design and Analysis of Simulation Experiments (International Series in Operations Research & Management Science Book 111)” Subjects and Themes:
- Subjects: ➤ Simulation methods - Probabilities - Statistics - Mathematical models - Operations research - Industrial engineering - Production engineering - Engineering design - Probability Theory - Statistical Theory and Methods - Mathematical Modeling and Industrial Mathematics - Operations Research and Decision Theory - Industrial and Production Engineering - Engineering Design
Edition Specifications:
- Number of Pages: 1 online resource (230 p.)
Edition Identifiers:
- The Open Library ID: OL26771947M - OL19141120W
- Online Computer Library Center (OCLC) ID: 209983560
- ISBN-13: 9780387718132
- ISBN-10: 0387718133
- All ISBNs: ➤ 0387718133 - 9780387718132 - 9786611138448 - 9781281138446 - 1281138444 - 9781601197665 - 1601197667
AI-generated Review of “Design and Analysis of Simulation Experiments (International Series in Operations Research & Management Science Book 111)”:
"Design and Analysis of Simulation Experiments (International Series in Operations Research & Management Science Book 111)" Table Of Contents:
- 1- Preface
- 2- Introduction
- 3- Black Box Metamodels
- 4- Low
- 5- rder Polynomial Regression
- 6- Metamodels and Designs: A Single Factor
- 7- Low
- 8- rder Polynomial Models and Designs: Multiple Factors
- 9- Low
- 10- rder Polynomial Models and Screening Designs: Hundreds of Factors
- 11- Kriging Metamodels
- 12- Latin Hypercube Sampling (LHS) and other Space
- 13- illing Designs
- 14- Cross
- 15- alidation of Metamodels
- 16- Conclusions and Further Research.
"Design and Analysis of Simulation Experiments (International Series in Operations Research & Management Science Book 111)" Description:
Harvard Library:
This is an advanced expository book on statistical methods for the Design and Analysis of Simulation Experiments (DASE). Though the book focuses on DASE for discrete-event simulation (such as queuing and inventory simulations), it also discusses DASE for deterministic simulation (such as engineering and physics simulations). The text presents both classic and modern statistical designs. Classic designs (e.g., fractional factorials) assume only a few factors with a few values per factor. The resulting input/output data of the simulation experiment are analyzed through low-order polynomials, which are linear regression (meta)models. Modern designs allow many more factors, possible with many values per factor. These designs include group screening (e.g., Sequential Bifurcation, SB) and space filling designs (e.g., Latin Hypercube Sampling, LHS). The data resulting from these modern designs may be analyzed through low-order polynomials for group screening and various metamodel types (e.g., Kriging) for LHS. In this way, the book provides relatively simple solutions for the problem of which scenarios to simulate and how to analyze the resulting data. The book also includes methods for computationally expensive simulations. It discusses only those tactical issues that are closely related to strategic issues; i.e., the text briefly discusses run-length and variance reduction techniques. The leading textbooks on discrete-event simulation pay little attention to the strategic issues of simulation. The author has been working on strategic issues for approximately forty years, in various scientific disciples--such as operations research, management science, industrial engineering, mathematical statistics, economics, nuclear engineering, computer science, and information systems. The intended audience is comprised of researchers, graduate students, and mature practitioners in the simulation area. They are assumed to have a basic knowledge of simulation and mathematical statistics; nevertheless, the book summarizes these basics, for the readers' convenience.
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