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Decision Support Methods

Code: CC3003     Acronym: CC3003     Level: 300

Keywords
Classification Keyword
OFICIAL Computer Science

Instance: 2023/2024 - 2S Ícone do Moodle

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 0 Official Study Plan 3 - 6 48 162
L:CC 83 study plan from 2021/22 3 - 6 48 162
L:F 0 Official Study Plan 2 - 6 48 162
3
L:G 0 study plan from 2017/18 2 - 6 48 162
3
L:IACD 1 study plan from 2021/22 3 - 6 48 162
L:M 6 Official Study Plan 2 - 6 48 162
3
L:Q 0 study plan from 2016/17 3 - 6 48 162

Teaching Staff - Responsibilities

Teacher Responsibility
João Pedro Pedroso Ramos dos Santos

Teaching - Hours

Theoretical classes: 1,71
Laboratory Practice: 1,71
Type Teacher Classes Hour
Theoretical classes Totals 1 1,71
João Pedro Pedroso Ramos dos Santos 1,71
Laboratory Practice Totals 3 5,13
João Pedro Pedroso Ramos dos Santos 3,42
Hugo Miguel Oliveira Romualdo Simões 1,71
Mais informaçõesLast updated on 2024-02-23.

Fields changed: Teaching methods and learning activities, Fórmula de cálculo da classificação final, Componentes de Avaliação e Ocupação, Tipo de avaliação, Observações, Melhoria de classificação

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)
Robert Fourer; AMPL. ISBN: 9780534388096
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)

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 materials and discussion of examples.
- Labs: problem solving, monitoring of assignments.
- In-class quizzes for self-evaluation (with computer-based evaluation).

Software

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

keywords

Physical sciences > Mathematics > Applied mathematics > Operations research

Evaluation Type

Evaluation with final exam

Assessment Components

designation Weight (%)
Exame 100,00
Total: 100,00

Amount of time allocated to each course unit

designation Time (hours)
Estudo autónomo 114,00
Frequência das aulas 48,00
Total: 162,00

Eligibility for exams

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

Calculation formula of final grade

Final examination: 100%

Examinations or Special Assignments

Practical assignments may carried out, at the student's wish; these will replace part of the exam assessment (see Notes at the end).

Special assessment (TE, DA, ...)

The same evaluation criteria is used for all students.

Classification improvement



Final exam.


Observations

The final exam includes a development part, to be solved on a computer. As an alternative to this part, students will be able to solve questions of the same kind in practical classes dedicated to it.

Jury: João Pedro Pedroso, José Paulo Leal
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