Complex Systems Modeling And Simulation

Catalog description

This is an introductory graduate course on complex systems and methods on how to model and simulate them. Such systems include several interacting components whose emerging behavior cannot be realized by knowing their components’ individual behaviors. The emphasis is on the application of such methods as discrete event modeling, agent-based modeling, network model, and cellular automata in real world systems. Examples includes industrial supply chain, healthcare, and and transportation. Individual assignments and group projects will be given based on the case studies identified in literature review and real world application. Students will use some software, such as Simio, for modeling and simulation. Graduate student status or senior status with instructor approval. Leveling courses may be required based upon student undergraduate degree. Course Learning Outcomes 1. Understand the notion of complex systems and their characteristics. 2. Learn various methods, such as discrete event and agent-based modeling, to model and simulate complex systems. 3. Use some relevant software for modeling and simulation. 4. Apply the lessons learned to carry out a modeling and simulation study on an assigned project. View Class Schedule