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Summary
Summary
This volume introduces computational and mathematical techniques for modeling, simulating, and analyzing the performance of various systems. Helps readers gain a better understanding of how systems operate and respond to change by: 1) helping them begin to model, simulate, and analyze simple-but-representative systems as soon as possible; and 2) whenever possible, encouraging the experimental exploration and self-discovery of theoretical results before their formal presentation. Features an approachable writing style that emphasizes concepts and insight without sacrificing rigor. Provides C software as source code for running simulations developed in the book, eliminating the need for readers to do all their programming from scratch. Emphasizes an algorithmic approach throughout. A useful reference for industrial engineers.
Table of Contents
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 |