Simulation and Scientific Computation

Academic year
Subject Area
Computer Science
Language of Instruction
Mode of Delivery
ECTS Credits
1st Cycle Studies

Recommended Prerequisites

Basic programming.

Teaching Methods

Lectures for presentation and discussion of concepts, principles, tools and case studies.

Practical classes for practical work using various techniques and tools.

Laboratory practices for development of assignments, the final project and discipline exercises.

Learning Outcomes

Simulation is a cross-discipline of a vast field of application. One of the fundamental objectives of the course is to acquire a body of knowledge and skills to enable before a specific situation, to develop a simulation model, implement it, validate it and use it correctly, taking into account the advantages and limitations of simulation. It is intended, in the context of a course in Computer Science, which constitutes an asset for future engineers, providing them with knowledge and skills that allow them to learn, compare and select the languages ​​/ development environments appropriate to simulation, enabling them to implement / adapt / customize complex simulation models, for which the use of existing environments or specific languages ​​is not satisfactory.

Also to a Computer Engineering professional it is also important to know, to identify the advantages and limitations and to use in concrete contexts and problems the main optimization approaches currently available.

Work Placement(s)



- Introduction to Simulation: system, model and simulation; types of models;

- Simulation of continuous models: systems for continuous simulation and numerical integration;

- Simulation of discrete models: simulation languages ​​and general purpose programming languages​;

- Statistical models in simulation;

- Generation of random numbers ;

- Queuing models; 

- Data analysis of simulation data and results;

- Verification and validation of simulation models.

Optimization: basic concepts, linear and nonlinear methods, with and without constrains.

Head Lecturer(s)

Maria José Patrício Marcelino

Assessment Methods

Practical assignments : 15.0%
Practical final project : 25.0%
Exam: 60.0%


J. Banks e J. S. Carson: Discrete-Event System Simulation, Prentice-Hall International, 1984.

Law, A. M. e Kelton, W.D.: Simulation Modeling and Analysis, McGraw Hill Book Company, 3ª edição, 2000.

Graybeal, W. e Pooch, U. W.: Simulation: Principles and Methods, Little Brown Company, 1980.

Bennett, B. S.: Simulation Fundamentals, Prentice-Hall International, 1995.

Garrido, J. M.: Object-Oriented Discrete-Event Simulation with Java, Kluwer Academic, 2001.

Rao, S.S.: Engineering Optimization, Theory and Practice, John Wiley & Sons, Fourth Edition, 2009.

Sundaram, R. K.: A First Course in Optimization Theory, Cambridge University Press, 1996.

Chinneck, J. W.: Practical Optimization: a Gentle Introduction, Carleton University, Canada, 2000. Accessed at