MS&E 323

Stochastic Simulation

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General Information

·Course Description

·Instructor, TAs and Staff

·Lectures, Problem Sessions and Office Hours


·Required Text






Course Description

Emphasis is on the theoretical foundations of simulation methodology. Generation of uniform and non-uniform random variables. Discrete-event simulation and generalized semi-Markov processes. Output analysis (autoregressive, regenerative, spectral, and stationary times series methods). Variance reduction techniques (antithetic variables, common random numbers, control variables, discrete-time, conversion, importance sampling). Stochastic optimization (likelihood ratio method, perturbation analysis, stochastic approximation). Simulation in a parallel environment.

Instructor, TAs and Staff

Please see Contact Info.

Lectures, Problem Sessions and Office hours

3:15 PM to 4:30 PM
Location: McCullough 122
3:15 PM to 4:30 PM
Location: McCullough 122

Office Hours:

Professor Glynn:

4:30 PM to 5:30 PM
Location: Terman 313            or by appointment (via email)

Xiaowei Zhang:

Friday 3:15 PM - 4:15 PM Location: Terman 321



MS&E 221 or equivalent

Required Text

Asmussen, S. and Glynn, P Stochastic Simulation: Algorithms and Analysis. Springer-Verlag, 2007.

Other useful references

Rubinstein, R.Y., Simulation and the Monte Carlo method. Wiley, 1981.

Ripley B.D., Stochastic Simulation. Wiley, 1987.

Henderson, S.G. and P.W. Glynn,Regenerative steady-state simulation of discrete-event systems. ACM Transactions on Modeling and Computer Simulation 11 313-345



For assignments, collaboration among students in the class is encouraged. You may discuss the problems with others, but you must write up solutions independently. Please include a small statement mentioning the names of the students with whom you discussed the problems, whether you benefitted from help or comments from the instructor or the CA, and whether you obtained something from a text or other source. 

Exams: No midterm

Final: Time: Wednesday, March 18, 12:15PM - 3:15 PM
  Location: McCullough 122


The course grade will be based on assignments (40%),  project (20%), and final exam (40%). 


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