Decision Support Methods

Code:

CC3003

Acronym:

CC3003

Level:

300

Keywords
Classification	Keyword
OFICIAL	Computer Science

Instance: 2022/2023 - 2S

Active?	Yes
Web Page:	http://www.dcc.fc.up.pt/~jpp/mad
Responsible unit:	Department of Computer Science
Course/CS Responsible:	Bachelor in Computer Science

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L:B	1	Official Study Plan	3	-	6	56	162
L:CC	95	study plan from 2021/22	3	-	6	56	162
L:F	0	Official Study Plan	2	-	6	56	162
			3
L:G	0	study plan from 2017/18	2	-	6	56	162
			3
L:IACD	0	study plan from 2021/22	3	-	6	56	162
L:M	2	Official Study Plan	2	-	6	56	162
			3
L:Q	0	study plan from 2016/17	3	-	6	56	162

Teaching language

Suitable for English-speaking students

Objectives

Students should:
1. Become familiar with the main decision and optimization problems.
2. Learn how to formalize optimization models in mathematical programming.
3. Master some methods used for their resolution.
4. Become familiar with existing languages and libraries for problem solving.
5. Develop skills to assess the computational complexity of problems.

Learning outcomes and competences

What you'll learn:
1. How to formalize rigorously practical decision situations.
2. An applied understanding of mathematical optimization and how to solve optimization models using available software.
3. How to implement all of these methods.
4. How to use simulation for decision making.

Working method

Presencial

Program

1. Introduction to operational research.
2. Mathematical programming: formulation and model classification.
3. Linear Programming. Duality.
4. Optimization in graphs and networks.
5. Project planning.
6. Discrete optimization.
7. Constraint programming.
8. Brief introduction to nonlinear programming.
9. Brief introduction to probabilistic models.
10. Simulation.

Mandatory literature

Hillier Frederick S.; Introduction to operations research. ISBN: 0-07-246121-7 (F. Hillier, G. Lieberman. Introduction to Operations Research. McGraw-Hill)

Complementary Bibliography

Winston Wayne L.; Operations research. ISBN: 9780534423629 (Operations research : applications and algorithms / Wayne L. Winston ; with cases by Jeffrey B. Goldberg)
Cormen Thomas H. 070; Introduction to algorithms. ISBN: 978-0-262-03293-3 (Introduction to algorithms / Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Stein)
Robert Fourer; AMPL. ISBN: 9780534388096

Comments from the literature

Software documentation:

GLPK documentation (http://www.gnu.org/software/glpk/glpk.html)
AMPL documentation (http://www.ampl.com)
SCIP documentation (http://scip.zib.de)
Constraint programming, Bockmayr and Hooker (http://web.tepper.cmu.edu/jnh/cp-hb.pdf)
GECODE http://www.gecode.org/
ECLIPSE http://www.eclipseclp.org/

Teaching methods and learning activities

- Lectures: presentation of the program topics and discussion of examples.
- Labs: problem solving and case studies.
- Assignments: development and presentation of practical projects by students.
- In-class quizzes (automatic correction).

Software

GLPK, AMPL, SCIP, GECODE, ECLIPSE (clp)

keywords

Physical sciences > Mathematics > Applied mathematics > Operations research

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	60,00
Trabalho prático ou de projeto	30,00
Teste	10,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	106,00
Frequência das aulas	56,00
Total:	162,00

Eligibility for exams

Attendance to practical classes (according to the University of Porto regulations).

Calculation formula of final grade

Final examination: 60%
In-class quizzes: 10%
Assignments: 30%
(Minimum grade at the final exam: 50%)

Internship work/project

There will be practical projects to be done in a group.

Special assessment (TE, DA, ...)

The same evaluation criteria is used for all students.

Classification improvement

Observations

Jury: João Pedro Pedroso, José Paulo Leal