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This course is methodologically focused and a continuation of ±õ³§·¡Ìý762 in Monte Carlo methods. The topics include, but are not limited to, Quasi-Monte Carlo, importance sampling and other advanced variance reduction approaches, derivative estimation, and simulation optimization in continuous and finite spaces. While the application of these techniques to actual simulations is practiced as assignments, the discussion on simulation software and programming will be minimal. A current topic research presentation/paper required.

Prerequisite: ISE/°¿¸éÌý762. Level knowledge of stochastic simulations; intermediate level familiarity with probability, statistics, and stochastic processes; comfortable coding knowledge with R/Matlab/Python to write small computer programs.

Typically offered in Spring only