Simulation Modeling and Analysis (Industrial Engineering and Management Science Series) [Hardcover]

Averill Law (Author), W. David Kelton (Author)

Book Description

ISBN-10: 0070592926 | ISBN-13: 978-0070592926 | Publication Date: December 30, 1999 | Edition: 3

This authoritative, comprehensive, and thoroughly up-to-date guide addresses all the important aspects of a simulation study, including modeling, simulation languages, validation, input probability distribution, and analysis of simulation output data. Full scale treatments of manufacturing systems simulation and simulation software and animation are also included along with useful and instructive case studies.

Editorial Reviews

About the Author

Averill Law (Tucson, AZ) is the founder of Averill M. Law & Associates. David Kelton (Cincinnati, OH) is a member of the faculty in the Department of Quantitative Analysis at the University of Cincinnati.

Product Details

• Hardcover: 800 pages
• Publisher: McGraw-Hill Science/Engineering/Math; 3 edition (December 30, 1999)
• Language: English
• ISBN-10: 0070592926
• ISBN-13: 978-0070592926
• Product Dimensions: 9.4 x 6.6 x 1.3 inches
• Shipping Weight: 2.4 pounds
• Average Customer Review: 4.6 out of 5 stars  See all reviews (10 customer reviews)
• Amazon Best Sellers Rank: #306,941 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

35 of 36 people found the following review helpful:

5.0 out of 5 stars Complete handbook of discrete-event simulation modeling, May 28, 1996

By A Customer

This review is from: Simulation Modeling and Analysis (McGraw Hill Series in Industrial Engineering and Management Science) (Hardcover)

If you're a working stiff now, but you were a student as I was, who sent stuff "down the memory hole," only to discover years later that you really needed to DO simulation--AARGHH!!!--then Law and Kelton's book is what you'll need close at hand.

The coverage is complete, including basic material on input probability distributions; random number generators and testing (most useful for students); and output data analysis. Solid, more practice-oriented chapters cover variance reduction, experimental design (could borrow more from Kleijnen's work), and software. A final chapter gives an in-depth approach to manufacturing simulation.

Unfortunately, some material is dated. For example, the software chapter addresses SIMAN/Cinema, which Systems Modeling Corporation has (thankfully!) replaced with ARENA (though SIMAN is still the basic simulation language). The book gives overviews of several simulation modeling languages; practitioners doing trade studies choosing "the corporate simulation tool" will be grateful for this ecumenicism.

The chapter covering validation and verification could afford to borrow more from current software engineering practice. Also, simulation modeling approaches for network computing and communications would comprise a good extra chapter (Law gives a short course on the subject).

Law and Kelton isn't light reading, but it's not a dry handbook, either. If you've had some light programming experience and vaguely recall your stats class, you'll find it approachable.

But this book is mostly the timeless stuff you'll need to get your work done. With the recent proliferation of inexpensive simulation software, companies are thrusting simulation work on engineers and system/software analysts who have little or no training. They should keep and use Law and Kelton's book, which provides both good skills and a roadmap to laying out and finishing a simulation project.

But I give Law and Kelton's book one of my highest compliments: Expensive technical books

20 of 23 people found the following review helpful:

5.0 out of 5 stars Better understanding, rather than point and click, February 5, 2001

By 

Sarawoot Chittratanawat - See all my reviews

This review is from: Simulation Modeling and Analysis (Industrial Engineering and Management Science Series) (Hardcover)

This book is the ground foundation of simulation modeling. Currently, only few books in simulation will spend pages and time, dedicated to the theoretical issues as good as this book. If you're tired of point-and-click or "how-to making one server queueing system" and you want to know the fundamental of simulation, you can't overlook this piece of jewel. I don't agree with one review that you have to understand statistics in order to get this book. Simulation is a probabilistic model. Using simulation without understanding statistics results in serious trouble since it will be only a toy (data), not a tool (information.

22 of 26 people found the following review helpful:

5.0 out of 5 stars A must read for anyone interested in simulation, August 15, 2000

By 

José A. Sánchez Villanueva - See all my reviews

This review is from: Simulation Modeling and Analysis (McGraw Hill Series in Industrial Engineering and Management Science) (Hardcover)

This is must read for simulation. It covers the background required for anyone to work on simulation and modeling. Its chapters about random-number generators, selecting right probability distributions and its parameters, output data analysis or variance reduction techniques are a must for anyone in this area. The treatment is easy to read but without sacrificing rigour. Nevertheless, a basic knowledge on statistics and probability is required. On the other hand, its chapters about modeling performed on fortran, C or pascal are outdated stuff since this software is outdated, but they are useful are a hands-on lesson on how simulation works and must be performed. All in all, a very profitable book.