Simulation

Code:

PRDEIG010

Acronym:

SIM

Keywords
Classification	Keyword
OFICIAL	Mathematics
OFICIAL	Computer Science

Instance: 2023/2024 - 2S

Active?	Yes
Responsible unit:	Department of Informatics Engineering
Course/CS Responsible:	Doctoral Program in Engineering and Industrial Management

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
PRODEGI	2	Syllabus since 2015/16	1	-	6	42	162

Teaching language

English

Objectives

The aim of this course unit may be considered in two perspectives. First of all, this course unit aims to present the area of modelling and simulation as an important resource and indispensible tool in the scientific method in order to test and validate concepts and theories, which are useful in almost all PhD projects. Subsequently, the presentation and discussion of recent techniques and methods of modelling and simulation should motivate the identification of problems and challenges, which make this area an excellent study subject in the domain of computer engineering. In more detail, the aims of this course unit are:

• to present the basic concepts of (computational) modelling and simulation and their diverse areas of application;
• to present the different phases of the life cycle of a simulation project, from the modelling phase to the analysis and application of results;
• to present the main types of models and their adequacy to the treatment of different problems, as well as the main simulation techniques.
• to extensively present and discuss the state of the art of recent technology in the area of modelling and simulation, by identifying the challenges, main areas of investigation and trends;
• to present the concept of agent-based simulation, with examples, and hands-on practice resorting to the NetLogo simulator.

Learning outcomes and competences

After the successful completion of this course unit, students should be capable of:

• Identifying problems, developing models and simulation projects;
• Analysing and applying simulation results;
• Including simulation techniques in the scientific method of different areas of investigation;
• Showing their knowledge of the main areas of interest and current challenges in the area of modelling and simulation;
• Using modelling and simulation tools;
• Designing and implementing tools and simulation environment for special or general purposes;
• Effectively using the NetLogo simulator to develop agent-based simulation projects.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

There is no mandatory prerequisite. Knowledge of (object-oriented) programming and statistics are desirable.

Program

1. Review and presentation of concepts:




• Simulation as an engineering methodology;


• Modelling (realism, abstraction) and types of models (normative, behavioural….);


• Data preparation and treatment;


• Modelling of complex systems and stochastic processes;




2. Simulation projects:




• Basic techniques of simulation: continuous, discrete and probabilistic simulation


• Simulation life cycle: data modelling, collection and preparation; test, calibration and validation of models, results analysis and implementation;


• Languages and environments of simulation.




3. Advanced topics in modelling and simulation:




• Object-oriented simulation;


• Distributed simulation;


• Visual interactive modelling and simulation;


• Realistic simulation;


• Intelligent simulation;


• Simulation environments and simulation of environments;


• Learning and evolutionary models;


• Optimisation methods in simulation;


• Heuristic and metaheuristic;




4. Agent-based modelling and simulation:




• concepts and modelling;


• social simulation;


• practical examples;


• NetLogo tutorial;




5. Applications of simulation.


6. Project in NetLogo.

Mandatory literature

Averill M. Law, W. David Kelton; Simulation modeling and analysis. ISBN: 0-07-059292-6
Jerry Banks, John S. Carson II, Barry L. Nelson; Discrete-event system simulation. ISBN: 0-13-218231-9
Brito, A.; Teixeira, J.; Simulação por computador: fundamentos e implementação em C e C++, Publindústria, 2001
Chung, C. ; Simulation Modeling Handbook: a practical approach, CRC Press, 2003

Complementary Bibliography

Vários Autores; Artigos de Conferências e Revistas Científicas na área de modelação e simulação, ACM SIGSIM, SCS, IEEE, Eurosis

Comments from the literature

Bibliography and references are mostly presented as recommended reading!

Teaching methods and learning activities

Passive learning is limited to the initial introduction of concepts. Students will be encouraged to deepen their knowledge by contextualising the state of the art and identifying recent trends. This component will comprise presentations of recent and relevant case studies of the different areas of study taught in this course unit.

However, the principal teaching method is based on an active learning, being directed to research and project. It aims to integrate students in practical activities, such as the use of simulation tools, implementation of ad-hoc simulators, reviews and readings of scientific papers, as well as structuring students’ knowledge by attending seminars and writing articles.

keywords

Technological sciences > Engineering > Simulation engineering

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Trabalho escrito	60,00
Trabalho laboratorial	40,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Elaboração de projeto	33,60
Estudo autónomo	42,00
Frequência das aulas	36,00
Trabalho de investigação	50,40
Total:	162,00

Eligibility for exams

Students should have a mark >=8 in all components of the continuous assessment.

Calculation formula of final grade

Continuous Assessment (CA) comprises:

• Preparation/presentation of seminars (S) (20%) 
• Preparation/presentation of tutorial (S) (20%) 
• Development of a simulation project (P) (60%) 

Final Project (P) comprises: 

• Oral presentation + demo (60%) 
• Written paper (40%) 

Therefore, Final Mark (FM) will be:

• FM = 0,2 * S + 0,2 * T + 0,6 * P 

The student cannot get a mark below 8 in each of the components, in which case he/she will fail the course.

Examinations or Special Assignments

• Writing up an article and its presentation;


• Preparation and presentation of seminars;


• Medium-size simulation project;


• Mid-term test.

Internship work/project

N/A

Special assessment (TE, DA, ...)

The assessment components are compulsory to all students, even to the ones who do not need to attend classes. The assessment activities will take place according to students’ availability and schedule.

Classification improvement

Students may improve their grades by improving one or more of the following assessment components:

• Simulation project;
• Writing up a paper and its presentation;
• Preparation/presentation of seminars.
• Mid-term test.

Observations

N/A