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Decision Support Methods

Code: CC3003     Acronym: CC3003     Level: 300

Keywords
Classification Keyword
OFICIAL Computer Science

Instance: 2017/2018 - 2S Ícone do Moodle

Active? Yes
Web Page: http://www.dcc.fc.up.pt/~apt/aulas/MAD/1718
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 56 162
L:CC 42 Plano de estudos a partir de 2014 3 - 6 56 162
L:F 0 Official Study Plan 2 - 6 56 162
3
L:G 0 study plan from 2017/18 3 - 6 56 162
L:M 1 Official Study Plan 2 - 6 56 162
3
L:Q 0 study plan from 2016/17 3 - 6 56 162
MI:ERS 8 Plano Oficial desde ano letivo 2014 3 - 6 56 162

Teaching language

Suitable for English-speaking students

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.

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 Programming languages and systems.
Introduction Markov Chains and queueing theory.

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)
Rossi Francesca 1962- 340; Handbook of constraint programming. ISBN: 0-444-52726-5 (Handbook of constraint programming / edited by Francesca Rossi, Peter van Beek, Toby Walsh))

Comments from the literature

For software:

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/

- Some chapters from
A. P. Tomás. Métodos de Apoio à Decisão. DCC-FCUP, 2003 (in Portuguese)

Teaching methods and learning activities

Lectures: presentation of the program topics and discussion of examples.

Labs: problem solving and case studies with experimental evaluation. Development of a practical project (team work).

Assignments: practical project; oral and written presentation.
 

Software

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

keywords

Physical sciences > Mathematics > Computational mathematics
Physical sciences > Computer science > Programming
Physical sciences > Mathematics > Applied mathematics > Operations research

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation Weight (%)
Exame 75,00
Trabalho laboratorial 25,00
Total: 100,00

Eligibility for exams

Required:
* Not to exceed the absence limit (25% of total number of estimated lab classes)

 

Calculation formula of final grade

Written examination (75%). One Lab Assignment (25%) - team project (TP).
A minimum grade of 8 at 20 is required in the final exam (tests).

If it fits in the academic calendar for 2017/2018, there will be two optional tests during the semester (TE1, TE2).  To attend TE2, it is required a minimum grade of 8.0/20.0 in TE1.  The second test covers all topics.  A minimum grade of 8.0/20.0 is required also.

The final grade is given by


    max(0.4*TE1+0.6*TE2, TE2, FinalExam)*.75 + 0.25* TP


Students do not need to take the final exam if max(0.4*TE1+0.6*TE2, TE2)*0.75 + TP*0.25 >= 9.5.

Internship work/project

There will be a practical project to be developed by a team.

Special assessment (TE, DA, ...)

The same evaluation criteria for all students.

 

Classification improvement



Final exam. Lab Assignment grade cannot be improved.



 
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