Optimization

Code:

PRODEM022

Acronym:

OPT

Keywords
Classification	Keyword
OFICIAL	Mechanical Engineering

Instance: 2023/2024 - 2S

Active?	Yes
Web Page:	http://www.fe.up.pt
Responsible unit:	Mathematics Section
Course/CS Responsible:	Doctoral Program in Mechanical Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
PRODEM	4	Syllabus since 2009/10	1	-	6	28	162

Teaching language

Portuguese and english

Objectives

The aim of the course is to provide students with knowledge of optimisation theory in general and the optimal design of mechanical engineering systems, in particular structures, thermo-mechanical systems and technological processes.

Learning outcomes and competences

At the end of lecture period the students should be able to perform the following aspects:
1 - Formulate optimization problems;
2 - Choice the appropriate optimization techniques aiming to solve engineering design problems;
3 – Develop of numerical optimization models using methodologies for optimal design;
4 - Analyse and validate the obtained results.

Working method

Presencial

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

Knowledge on Methematics and Mechanical Engineering.

Program

The optimization framework in the context of the engineering science. Definition of the programmatic contain and student initiation in the formulation and language of the optimization.
Review of fundamental concepts. Single-variable minimization.
Multivariable optimization with no constraints: basic concepts and numerical solution methods.
Multivariable optimization with constraints: presentation based on previous classification of the optimization techniques. Mathematical programming and optimality criteria search methods.
Sensitivity analysis and gradient calculation: analytical, semi-analytical and numerical methods.
Optimization methods based on evolutionary search. Genetic algorithms: definition of the main aspects.
Memetic algorithms: definition of the main aspects.
Comparison of different optimization methods for the same problem.
Advanced topics: swarm intelligence optimization methods and multi-objective optimization.

Mandatory literature

Carlos Alberto da Conceição António; Otimização de sistemas em engenharia. ISBN: 978-989-901-734-4 ((www..engebook.pt))
Vanderplaats, Garret N.; Numerical Optimization Techniques for Engineering Design. ISBN: 0-07-066964-3

Complementary Bibliography

Rao, Singiresu S.; Engineering Optimization, Theory and Practice, John Wiley & Sons,Inc., New York, 1996. ISBN: 0-471-55034-5
Jasbir S. Arora; Introduction to optimum design. ISBN: 0-07-100123-9
David E. Goldberg; Genetic algorithms in search, optimization, and machine learning. ISBN: 0-201-15767-5
Carlos Alberto da Conceição António; Optimization of mechanical systems - fundamentals and algorithms. ISBN: 978-989-53416-0-3

Teaching methods and learning activities

The teaching methodology is based on the implementation of the relationship between different topics of the program. The objective is to increase the student assimilation of matter. The students will be encouraged to analyse papers covering the optimization topics aiming the development of small optimization models or the revision of the state of art.

keywords

Technological sciences > Engineering
Physical sciences > Mathematics
Technological sciences > Engineering > Project engineering

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Trabalho escrito	45,00
Apresentação/discussão de um trabalho científico	20,00
Teste	35,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Elaboração de relatório/dissertação/tese	15,00
Estudo autónomo	45,00
Frequência das aulas	30,00
Trabalho de investigação	32,00
Apresentação/discussão de um trabalho científico	20,00
Trabalho laboratorial	20,00
Total:	162,00

Eligibility for exams

Terms of frequency: 1)To attain frequency, the student must not exceed the absence limit allowed in the General Evaluation Rules of FEUP;
2)Develop and present at least one of the planned theoretical and practical works, including report.

Calculation formula of final grade

(1) Carrying out theoretical and practical research and computational development work on classical optimisation methods;
(2) Carrying out theoretical and practical research and computational development work on evolutionary optimisation research methods;

The student must submit an overall report containing the theoretical content, algorithmic description and results of the two assignments (1) and (2). This global report has a weight of 45% in the final grade.
The work will be presented and discussed with the lecturer. This discussion of the results has a weight of 20% in the final grade.

(3) A written test with a weight of 35% in the final grade.

The final grade is the weighted average of the three components defined above.

Examinations or Special Assignments

Two theoretical and practical research works with report.

Internship work/project

N/A

Special assessment (TE, DA, ...)

The same type of assessment as for normal students except for attainment.

Classification improvement

The student may choose to improve each or both of the theoretical and practical assignments that are part of the assessment. In any case, the legal procedures of the current General Evaluation Rules must be respected.

Observations

In addition to the reference bibliography, students will have access to supporting texts on each topic of the program to teach.