Simulation Modeling and Analysis (Mcgraw-hill Series in Industrial Engineering and Management)

I have used Simulation Modeling and Analysis for many years, first in graduate school and then for my work. It has an extensive discussion of most major topics in discrete-event simulation, including validation of models, choosing probability distributions to represent system randomness, designing and analyzing experiments, random number generation, and simulation software. It’s really valuable to have so much information on simulation in one place, as well as many references for future study. The book is also very error free. The fifth edition has a new chapter on agent-based simulation, which taught me a great deal about the subject including its relationship to discrete-event simulation.

The book is in pretty good shape

This was the textbook for my simulation class, and I didn’t find it very interesting. It didn’t increase my interest in the course like other sources did.

Just what i needed.

Arrived perfectly. As to the contents, explanations are a little murky at times. It asks you to skip to certain sections at explanations so you’re jumping back and forth and sometimes the relationship is not clear at first but take this part w a pinch of salt (maybe I’m dumb). Very useful diagrams.

I finally started using the book for school and the book is multiple pieces due to the spine being split.

This is a heavy book. It has fine print. Reputable author. I never used the book for the Simulation​ Modeling class I took.

I received the 5th Ed. as an evaluation copy and compared to the 2nd Ed which I've owned since the early 90's, the 5th Ed. provides no additional value. The contents of the 5th Ed. are nearly identical to the 2nd (and presumably 3rd and 4th Eds.). The book's notable chapters are those on statistical treatment of model input variables and output analysis and these are of value to modelers at all experience levels. Little discussion is spent on multivariate analysis, but that can be excused because it's a book all in itself. The rest of the text struggles to describe simulation model design using antiquated approaches. Simulation model design and software have evolved exponentially in the last 30 years - this book's concepts have not. Consequently, the text is an odd dichotomy of needlessly complicated topics like how to write a random number generator (which you needed to do long ago) and another chapter reviewing commercial simulation packages.The text would benefit from modern code examples in languages that students are learning now like Python, Java, or mathematical languages like Julia. For a book on statistics, there's a surprising lack of examples using languages such as R which is the modern gold standard for statistical analysis. Although the 5th Ed have updated their models from Fortran, they're still using functional C programs. The authors barely mention object-oriented programming and their model design unfortunately reflects this. Modern simulation models haven't followed these software designs in decades. The last chapter on agent-based modeling is a weird mish-mash of topics having nothing to do with ABM and there are no AMB code examples. Readers wanting to learn more about these topics would be better served by an appropriate review article.I cannot recommend the 5th Ed of this book. The only useful chapters on statistics are available in the early editions.