SIMULATION MODELING AND ANALYSIS

Credit Hours: 3 · Undergraduate Upper-Level

This course introduces simulation techniques that uses statistical sampling, probability models and computational tools to study complex stochastic systems arising in service operations, healthcare, telecommunications, production, logistics, inventory and financial systems. Topics covered include generating random objects (random variables and stochastic processes, discrete-event systems), input and output analysis, steady-state simulation, variance-reduction methods, rare-event simulation, Markov chain Monte Carlo methods, and simulation-based optimization. The course lectures are supplemented with programming components in homework and projects. Graduate/Undergraduate Equivalency: CMOR 551 . Recommended Prerequisite(s): MATH 212 , ( STAT 310 or STAT 311 or STAT 418 ), (CAAM 334 or 303 or CAAM 335 or CMOR 302 ), and MATH 302