Class Systems Architecture and Simulation

It provides knowledge, skills and tools for the analysis of complex problems, characterized by their dimension, uncertainty and risk, in Industrial Engineering and Management. Its scope includes the application of different methods for structuring, modeling, simulation and optimization of systems, towards decision aiding.

Introduction and review of basic concepts

Modeling paradigms and model structuring

Discrete event simulation models, including:

• Architecture based on events, activities, and processes

• Random sequence generation techniques and Monte Carlo methods

• Software and case studies

System Dynamic modeling, including:

• Architecture and basic elements (cause-effect relationships, feedback cycles, causal loop and stock-and-flow diagrams)

• Basic forms of feedback loops, typical behaviors of response variables, nonlinear relationships, accumulation and delays

• Software and case studies

Agent-based modeling, including:

• Architecture of agents

• Relations with other modeling paradigms.

• Software and case studies

Multi-method modeling, including:

• Multi-method architecture

• Multi-method modeling, model validation and optimization

• Software and case studies

The Innovative Methodologies of the Curricular Unit "Systems Architecture and Simulation" include modern and creative pedagogical approaches aimed at improving the way students acquire knowledge in this subject. It involves the use of educational techniques and advanced technologies to promote a deeper understanding of the concepts of systems architecture and its simulation. Examples of innovative methodologies include the use of interactive simulations, real-world case studies, online collaboration and group discussions to stimulate students' active participation and facilitate the practical application of the concepts learned. The aim is to create an engaging and effective learning experience that prepares students to face the challenges of systems architecture and simulation competently and creatively.

• Bala, B. K., Arshad, F. M., Noh, K. M. (2017). System dynamics. Springer Texts in Business and Economics. Springer.
• Taylor, S. (Ed.). (2014). Agent-based modeling and simulation. Springer.
• Brailsford, Sally, Churilov, Leonid, Dangerfield, Brian (Eds.). (2014). Discrete-event simulation and system dynamics for management decision making. John Wiley & Sons