What's New in the Fifth Edition
Chapter 1, Introduction to Simulation, adds abstracts of many real cases.
Chapter 2, Simulation Examples, begins with 3 simple spreadsheet simulations that cover the basics -- how to obtain random numbers and generate a random variable from a simple discrete distribution, plus a few key concepts such as activities and system state, after which the instructor can choose among any of 9 examples in coin tossing, queueing, inventory policies, reliability and project activity networks to illustrate the basics of simulation modeling as well as experimentation with a simulation model.
Chapter 4, Simulation Software, updates the material on simulation software.
Chapter 6, Queueing Models, adds a case study on rough-cut modeling of queueing systems prior to simulation and replaces the Maple examples with Matlab. The Excel spreadsheet, QueueingTools.xls computes queueing performance measures.
Chapter 7, Random-Number Generation , and Chapter 8, Random-Variate Generation now come with a spreadsheet, RandomNumberTools.xls , that contains implementations in Visual Basic for Applications (VBA) of a long-period random-number generator and random-variate generators for all the statistical distributions in Chapter 8.
Chapter 9, Input Modeling replaces the core example with a series of brief examples that illustrate the difficulties that can occur in input modeling. Examples using Maple were replaced by Matlab code.
Chapters 11 and 12 have been renamed to Estimation of Absolute Performance and Estimation of Relative Performance, respectively. The chapters come with updated examples and a spreadsheet SimulationTools.xls that implements many of the statistical procedures in these two chapters. The material in Chapter 12 on metamodeling now emphasizes issues that are special to simulation experiments as opposed to regression analysis in general.
Chapter 14 integrates the discussion of computer systems and networking, and provides new material on wirelessly networked systems. We describe models of how users move about in a domain and highlight a pitfall many have suffered using the random waypoint model. We also include material showing how radio propagation is modeled (so as to determine when broadcast messages are actually received), and point out the range of complexities : from the very simple free-space model, to the computationally intensive ray-tracing model.