The aim of this course is to enable students to analyze complex systems and model them through simulation. In particular, the aim is to model the processes encountered in production, service, logistics and information technology systems, to understand the effect of randomness and to use simulation in the decision-making process.

This course teaches the simulation modeling of stochastic processes and queuing systems. Event-based simulation applications are performed using Python, R or Excel. Students analyze system behaviors by developing various scenarios and create simulation-based decision support models.