This course is about simulation methods for measuring performances of complex systems, covering both practical tools in modeling discrete event dynamic system (DEDS) and theoretical formalization of the optimization process. Topics include balance equation for probability flow equation, Petri net, queuing theory, generalizaed semi-Markov process & Markov chain, random number generation and alias method, ordinal optimization, no free lunch theorem, sample-path analysis, Markov decision process and reinforcement learning.