Simulation Modeling and Analysis

Catalog description

Introduction to Monte Carlo simulation and discrete-event simulation. Topics include: random variate and process generation; data-driven distribution modeling; input and output analysis; modeling, analysis and optimization of complex systems. Emphasizes tools and techniques needed in practice; in particular, modeling in simulation in Python, as well as commercial discrete-event simulation languages.