Discrete-Event Simulation: A First Course

Abstract

1. Models 1.1. Introduction 1.2. A Single-Server Queue 1.3. A Simple Inventory System 2. Random Number Generation 2.1. Lehmer Random Number Generation: Introduction 2.2. Lehmer Random Number Generation: Implementation 2.3. Monte Carlo Simulation 2.4. Monte Carlo Simulation Examples 3. Discrete-Event Simulation 3.1. Discrete-Event Simulation 3.2. Multi-Stream Lehmer Random Number Generation 3.3. Discrete-Event Simulation Models 4. Statistics 4.1. Sample Statistics 4.2. Discrete-Data Histograms 4.3. Continuous-Data Histograms 4.4. Correlation 5. Next-Event Simulation 5.1. Next-Event Simulation 5.2. Next-Event Simulation Examples 5.3. Event List Management 6. Discrete Random Variables 6.1. Discrete Random Variables 6.2. Generating Discrete Random Variables 6.3. Discrete Random Variable Applications 6.4. Discrete Random Variable Models 6.5. Random Sampling 7. Continuous Random Variables 7.1. Continuous Random Variables 7.2. Generating Continuous Random Variables 7.3. Continuous Random Variable Applications 7.4. Continuous Random Variable Models 7.5. Nonstationary Poisson Processes 7.6. Acceptance-Rejection 8. Input Modeling 8.1. Error in Discrete-Event Simulation 8.2. Modeling Stationary Processes 8.3. Modeling Nonstationary Processes 9. Output Analysis 9.1. Interval Estimation 9.2. Monte Carlo Estimation 9.3. Finite-Horizon and Infinite-Horizon Statistics 9.4. Batch Means 9.5. Steady-State Single-Server Service Node Statistics 10. Projects 10.1. Empirical Tests of Randomness 10.2. Birth-Death Processes 10.3. Finite-State Markov Chains 10.4. A Network of Single-Server Service Nodes Appendices: A. Simulation Languages B. Integer Arithmetic C. Parameter Estimation Summary D. Random Variate Models E. Random Variate Generators F. Correlation and Independence References

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