| Lectures 1-3 |
General Overview
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mechanics of the class
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what, why and how of simulation
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examples
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components of a simulator
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project topics
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Law and Kelton: Sections 1.1, 1.2, 1.7, 5.1, 5.2, 5.4,
5.5 |
| Lecture 4-10 |
Input generation :
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Generating independent uniform [0,1] randon variables
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Tests for uniformity and independence
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Tests for validity for input assumptions
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Generating independent random variates
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Generating correlated random variates
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Generating some useful variates
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Generating arrival processes
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Law and Kelton: Chapter 7,8 |
| Lecture 10-15 |
Simulator design :
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Discrete event approach
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Continuous-time Markov chain approach
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Monte Carlo methods
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Law and Kelton: Sections 1.3, 1.4, 1.5, 1.6, 1.8 |
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Midterm |
Up until March 3rd (Wed) |
| Lecture 16-20 |
Output Analysis :
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Transient measures
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Steady state measure
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Steady state cyclical measures
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Law and Kelton: Chapter 9 |
| Lecture 21-25 |
Increasing statistical efficiency :
variance reduction methods
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Antithetic and control variates
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Conditioning and Stratification
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Inportance sampling
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Common random variates
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Law and Kelton: Chapter 11 |
| Lecture 26 |
Conclusion, more advanced materials and classes at Columbia |
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Final Exam |
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Projects to be handed in |
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