Decision Support Methods

Code:

CC330

Acronym:

CC330

Keywords
Classification	Keyword
OFICIAL	Computer Science

Instance: 2013/2014 - 2S

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

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L:AST	0	Plano de Estudos a partir de 2008	3	-	5	-
L:B	0	Plano de estudos a partir de 2008	3	-	5	-
L:CC	33	Plano de estudos de 2008 até 2013/14	2	-	5	-
			3
L:F	0	Plano de estudos a partir de 2008	3	-	5	-
L:G	1	P.E - estudantes com 1ª matricula anterior a 09/10	3	-	5	-
		P.E - estudantes com 1ª matricula em 09/10	3	-	5	-
L:M	0	Plano de estudos a partir de 2009	3	-	5	-
L:Q	0	Plano de estudos Oficial	3	-	5	-
MI:ERS	9	Plano de Estudos a partir de 2007	3	-	5	-

Teaching language

Portuguese

Objectives

Students should:
- get familiar with techniques of operations research and constraint programming
and their application to modeling and solving deterministic and stochastic decision and optimization problems.
- develop skills for understanding computational complexity of concrete problems, and choosing algorithms, programming languages and libraries/APIs for solving them.

Learning outcomes and competences

Master the main techniques in optimization and simulation.

Working method

Presencial

Program

Formulation of formal models for decision problems.
Linear Programming: the Simplex method; transportation and assignment problems. Network problems: shortest and longest paths, spanning trees, max flow, project management (Critical Path Method).
Introduction to Integer Programming and Combinatorial Optimization.
Methods and techniques for reducing the search space: dynamic programming, constraint propagation, local consistency enforcement, branch-and-bound, cutting planes, symmetry breaking, model reformulation, approximation algorithms (greedy strategies) and local search.
Constraint (Logic) Programming languages and systems.
Introduction Markov Chains and queueing theory.

Mandatory literature

000002470. ISBN: 978-0-07-113989-2
000002720. ISBN: 9780471283669
A. Niederlinski; A Quick and Gentle Guide to Constraint Logic Programming via ECLiPSe, Economic University in Katowice, Poland, 2011. ISBN: 978-83-62652-08-2

Complementary Bibliography

000080915. ISBN: 978-1-55860-890-0
000002200. ISBN: 978-0-262-13341-8
000074199. ISBN: 9780262032933 hbk
000089055. ISBN: 0-444-52726-5

Teaching methods and learning activities

Lectures: Exposition of the program topics and discussion of examples using a computer connected to a multimedia projector.

Labs: problem solving and case studies with experimental evaluation.

Software

GLPK: GNU Linear Programming Kit
The ECLiPSe Constraint Programming System (http://www.eclipseclp.org/)

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Defesa pública de dissertação, de relatório de projeto ou estágio, ou de tese	25,00
Exame	75,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Elaboração de relatório/dissertação/tese	25,00
Estudo autónomo	50,00
Frequência das aulas	50,00
Total:	125,00

Eligibility for exams

Students cannot exceed the absence limit (25% of total number of estimated lab classes)

Calculation formula of final grade

Lab Assignment (25%).
Written examination (75%).
A minimum grade of 9.5 at 20 is required in the final exam.

Special assessment (TE, DA, ...)

The same evaluation criteria for all students.

Classification improvement

Lab Assignment grade cannot be improved.