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This unique book develops the application of experimental statistical designs and analysis to discrete-event simulation modeling. It takes a practical perspective and orients the reader with examples of the role of simulation in modeling a system. The stages and steps for applying simulation are discussed by focusing on the important role of statistics. Examples are given about how to design an experiment using techniques such as classical designs, group screening, polynomial decomposition, and Taguchi designs. Using the statistical techniques discussed, a sound simulation model can be built and adequately tested before implementation.
The book also shows how simulation results can be generalized by discussing in full the growing emphasis on simulation metamodeling. Examples of this approach are presented to show that reliable and simple models could be easily obtained. Furthermore, such models are applied within a decision framework to optimize the system of interest. This expands the power of simulation from being purely descriptive of the system to being a prescriptive model. The reader is exposed to potential problems and how such problems may be harnessed. Although the book discusses statistical techniques, it is written so as to be comprehensible to anyone with a basic background in statistics. The book is a good resource for consultants and simulation practitioners; it can also be used as a textbook for classes in simulation.
List of contents
The Art of Modeling
Construction of Simulation Models
Data Collection and Analysis Using Descriptive Statistics
Data Analysis Using Inferential Statistics
Generation of Random Numbers and Random Variables
Tests for the Goodness-of-Fit of Random Number Generators
Modelling of Basic Queuing Systems
Steady State Output Analysis
Classical Factorial Designs and Regression Metamodels
Toguchi Designs
Group Screening
Polynominal Decomposition
Appendix
About the author
CHRISTIAN N. MADU is Professor of Management Science at the Lubin Graduate School of Business, Pace University, New York. He has published extensively on the applications of statistics and probability theory to simulation modeling in journals such as
Decision Science,
IIE Transactions,
Journal of Operational Research Society,
European Journal of Operational Research,
Computers and Operations Research, and
International Journal of Production Research. In addition, Dr. Madu has published two other books with Quorum,
Strategic Planning in Technology Transfer to Less Developed Countries, and
Management of New Technologies for Global Competitiveness.
CHU-HUA KUEI is Assistant Professor of Management Information Systems and Total Quality Management at Monmouth College, West Long Branch, New Jersey./He has published several articles on simulation experiments in journals such as
Computers and Operations Research,
European Journal of Operational Research,
International Journal of Production Research and others. With Dr. Madu he also served as a co-Guest Editor of a special issue of International
Journal in Computer Simulation titled Simunlation Metamodeling of Production Systems.
