About this book
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.
- Book Title Design and Analysis of Simulation Experiments
- Series Title International Series in Operations Research & Management Science
- DOI https://doi.org/10.1007/978-0-387-71813-2
- Copyright Information Springer Science+Business Media, LLC 2008
- Publisher Name Springer, Boston, MA
- eBook Packages Mathematics and Statistics Mathematics and Statistics (R0)
- Hardcover ISBN 978-0-387-71812-5
- Softcover ISBN 978-1-4419-4415-3
- eBook ISBN 978-0-387-71813-2
- Series ISSN 0884-8289
- Edition Number 1
- Number of Pages XIV, 220
- Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
Probability Theory and Stochastic Processes
Statistical Theory and Methods
Mathematical Modeling and Industrial Mathematics
Operations Research/Decision Theory
Industrial and Production Engineering
- Buy this book on publisher's site
"This work represents a lucid, comprehensive, authoritative, and highly informative presentation of the techniques and methodology associated with simulation experimentation. The book is ‘lucid’ because, as the word implies, it sheds light on the subject matter of simulation experimentation and optimization; it is ‘comprehensive’ because it addresses all of the essential topics in the field; it is ‘authoritative’’ because it captures the essence of the best research in the field, as evidenced by its more than 400 authoritative citations; and it is ‘‘informative’ in that it distills the most important scholarship of the last six decades into a 210-page study of the DASE field. Jack Kleijnen has once again produced a cutting-edge approach to the design and analysis of simulation experiments. His 1974–75 books were an incisive compilation of statistical methodology in simulation and introduced the term metamodeling to the lexicon of simulation experimentation. His 2008 volume Design and Analysis of Simulation Experiments promises to popularize the term DASE in the same way. Many of us who specialize in the field of simulation experimentation and optimization have avidly followed Kleijnen’s writings for almost four decades. This latest work leads the way in this endeavor, and is a vital addition to the important scholarship in the field." (William E. BILES, JASA, June 2009, Vol. 104, No. 486)