This book provides a basic treatment of discrete-event simulation, one of the most widely used operations research and management science tools for dealing with system design in the presence of uncertainty. Proper collection and analysis of data, use of analytic techniques, verification and validation of models and the appropriate design of simulation experiments are treated extensively. Readily understandable to those having a basic familiarity with differential and integral calculus, probability theory and elementary statistics. Includes simulation in C++, the latest versions of the most widely used packages, and features of simulation output analysis software. Covers properties, modeling and random-variate generation from the lognormal distribution. Clarifies the difficult distinctions between terminating and steady-state simulation, and between within- and across-replication statistics. Contains up-to-date treatment of simulation of manufacturing and material handling systems. Emphasizes the hierarchical nature of computing systems, and how simulation techniques vary, depending on the level of abstraction. For readers wanting to learn more about system simulation.
I've been using this as reference for a CS class on simulation, and it has been a __life_saver__. Some authors just assault you with equations, then wave their hands in the air as an explanation. But here, everything is in plain English. And while the material's not easy, it can be grasped after some close reading. Very trite, but it's made the subject fun. PLUS: Solutions for the exercises are available online with some clever Googling. Check it.
I read this book for self-study to get an idea as to how discrete event simulation worked. This book was pretty good for that. The application chapters at the end of the text weren't terribly useful as it seems like they exist to motivate a lab section or assignments in a university course. Some of the statistics-oriented sections did full calculation demos in the text. While a good idea in principle, these also dragged on quite a bit. Still it was a good, complete text for getting a handle on these concepts.
This is a fairly good book on the subject of experimental modeling and simulation. It does help go have a background in stats and there is some calculus in the book, not to mention a strong understanding of programming.