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Presentation
Presentation
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.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Master Degree | Semestral | 6
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Year | Nature | Language
Year | Nature | Language
1 | Mandatory | Português
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Code
Code
ULHT6606-24230
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
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
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Objectives
Objectives
To develop familiarity and critical understanding of core concepts and techniques of computer simulation (discrete-event and system dynamics), along with support tools (namely specialized software packages). To develop an informed understanding of simulation frameworks for: problems formulation and solving; model structuring and implementation; design of experiments, results analysis and evaluation. To develop the ability to relate concepts to practice and skills to model real-world complex problems, involving uncertainty and risk, in a structured way and to provide sound recommendations. To promote soft skills (e.g., communication of analysis performed).
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Teaching methodologies and assessment
Teaching methodologies and assessment
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.
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References
References
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
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Office Hours
Office Hours
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Mobility
Mobility
No