Simulation

Recommended Prerequisites

English (main language) or Portuguese

Teaching Methods

Teaching is organised as two complementary components, theory and practice. Lectures (T) are mainly of an expository nature, but are also used to answer questions of general interest to the class. Practical (PL) sessions aim to consolidate the concepts presented in the lectures through pencil-and-paper exercises and the implementation of simulation models in software. A practical assignment involving the modeling and simulation of simplified realistic systems using appropriate simulation software is also proposed and assessed.

Learning Outcomes

With this curricular unit, it is intended to provide the students with the knowledge and competencies required to enable them to, given a concrete situation, develop an appropriate simulation model, and to implement, calibrate, validate, and use such a model correctly while considering both the benefits and the limitations of simulation as a methodology. It is also intended to motivate the students to the importance of considering, not only data, but also the internal dynamics of the various systems of interest, whether physical, cybernetic, social, or of some other nature.

Work Placement(s)

No

Syllabus

1. Systems, models, and simulation
2. Continuous systems
a. Modelling
b. Representation
c. Numeric integration of ODEs
d. Numeric integration of PDEs
3. Discrete-event systems
a. Representation: finite automata, activity-cycle diagrams, Petri nets, interacting processes
b. Queueing models
c. Simulation methods: event scheduling, activity scanning, process interaction
4. Pseudo-random numbers
a. Generation
b. Quality
c. Non-uniform random variate generation (continuous and discrete)
d. Monte Carlo simulation
5. Construction, verification and validation of discrete-event system models
a. Selecting input probability distributions
b. Model verification
c. Model calibration and validation
6. Analysis of simulation results
a. Evaluation of a single model
b. Comparison of two or more models
c. Variance-reduction techniques
7. Hybrid systems

Head Lecturer(s)

Fernando José Barros Rodrigues da Silva

Assessment Methods

Assessment
Project: 35.0%
Exam: 65.0%

Bibliography

François E. Cellier and Ernesto Kofman, Continuous System Simulation, Springer, 2006.
Hartmut Bossel, Modeling and Simulation, A K  Peters, 1994.
Christos G. Cassandras and Stéphane Lafortune, Introduction to Discrete Event Systems, Springer, 2007.
J. Banks, J. S. Carson, B. L. Nelson, and D. Nicol, Discrete-Event System Simulation, 5th ed., Prentice Hall, 2010
Averill M. Law, Simulation Modeling and Analysis, 5th ed., McGraw Hill, 2014.
Michael Pidd, Computer Simulation In Management Science, 5th ed., Wiley, 2006.
Ronald T. Kneusel, Random Numbers and Computers, Springer, 2018
James E. Gentle, Random Number Generation and Monte Carlo Methods, 2nd ed., Springer, 2003.