Optimization

Code:

2MADSAD03

Acronym:

O

Keywords
Classification	Keyword
OFICIAL	Management Studies

Instance: 2013/2014 - 1S (of 09-09-2013 to 20-12-2013)

Active?	Yes
Responsible unit:	Management
Course/CS Responsible:	Master in Modeling, Data Analysis and Decision Support Systems

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MADSAD	35	Bologna Official Syllabus	1	-	7,5	56	202,5

Teaching language

Portuguese

Objectives

Introduce the issues of optimization in the context of combinatorial optimization problems;

Introduce and describe some optimization methods, both exact (dynamic programming) and approximate: heuristics (constructive and local search) and metaheuristics (genetic algorithms);

Implement some of these optimization methods using software.

Learning outcomes and competences

Students should be capable of applying the concepts and techniques taught to specific (combinatorial optimization) problem contexts.

In addition, students will be able to implement computationally some of these techniques, in order to solve larger and/or more complex problems, which eventually may be part of the dissertation.

Working method

Presencial

Program

Combinatorial Optimization

Exact solution methods (dynamic programming)

Approximate solution methods, both heuristic and metaheuristic

Implementing some of these methods in MATLAB

Mandatory literature

Glover, Kochenberger (eds); Handbook of Metaheuristics, Springer (Kluwer)
Dimitri P. Bertsekas; Dynamic Programming and Optimal , Athena Scientific, 2005

Teaching methods and learning activities

Theoretical exposition along with practical examples.

Some lab sessions, where the MATLAB software will be used to implement some of the optimization techniques.

Software

MATLAB

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Participação presencial	10,00
Teste	50,00
Trabalho escrito	40,00
Total:	100,00

Calculation formula of final grade

Época normal:

Weighted average of the above specified components (0.1 classes + 0.4 assignment +0.5 test).

If a student does not attend the test or does not hand in the assignment, a score of 0 will be given to that test or assignment. Students will fail this course (with a final score of 8) if they attain a score lower than 6 on the test or on the assignment, regardless of the overall weighted score.

 

There is specific procedure to be followed regarding the assignment. This will be explained in the first lecture.

Época de recurso:

Final exam. The assignment mark may be used (with a 40% weight on the final mark) if the student requests it.

Special assessment (TE, DA, ...)

In accordance with FEP.UP's evaluation regulations.

Classification improvement

In accorance with FEP.UP's evaluation regulations.