42.525 Digital Twins in Data-driven Decision

Course description

This course will introduce students to various aspects of analysing complex systems using digital twins. Four main forms of simulation of systems namely event simulation for solving queuing and inventory problems, multi-agent system simulation involving agent-based simulation for solving complex engineering problems, Monte Carlo simulation with applications in financial engineering, and System Dynamics to model physical and business phenomena.

Case studies with applications to airport facility design, financial engineering, healthcare (A&E), and inventory management will be discussed. Implementation of simulation techniques, comparison of competing designs and statistical analysis of output will be conducted using a variety of programming tools including AnyLogic, Arena, Flexsim and R.

Instructor

Bhargav Sreepathi

Number of credits: 12