This well established text for senior graduate/postgraduate courses in Production Engineering and Computer Science in its fourth edition is extensively updated and revised in its contents, besides, addition of a separate chapter on simulation of Computer Networks. It provides a basic treatment of discrete-event simulation, including the proper collection and analysis of data, the use of analytic techniques, verification and validation of models, and designing simulation experiments. It offers an up-to-date treatment of simulation of manufacturing and material handling systems, computer systems, and computer networks. The new edition incorporates additional models-the beta and negative binomial distributions and the nonstationary Poisson process. Several alternatives are also discussed in the presentation of output analysis.

Table of Contents

Preface.

About the Authors.

Part I: INTRODUCTION TO DISCRETE-EVENT SYSTEM SIMULATION-
1. Introduction to Simulation.
2. Simulation Examples.
3. General Principles.
4. Simulation Software.

Part II: MATHEMATICAL AND STATISTICAL MODELS-
5. Statistical Models in Simulation
6. Queueing Models. Part III: RANDOM NUMBERS-
7. Random-Number Generation.
8. Random-Variate Generation.

Part IV: ANALYSIS OF SIMULATION DATA-
9. Input Modeling.
10. Verification and Validation of Simulation Models.
11. Output Analysis for a Single Model.
12. Comparison and Evaluation of Alternative System Design.

Part V: APPLICATIONS-
13. Simulation of Manufacturing and Material-Handling Systems.
14. Simulation of Computer Systems.
15. Simulation of Computer Networks.

Appendix.

Index.