Decision Support

Code:

PDEEC0044

Acronym:

DS

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2011/2012 - 1S

Active?	Yes
Web Page:	http://paginas.fe.up.pt/~mac/ensino/DS20112012.html
Responsible unit:	Department of Industrial Engineering and Management
Course/CS Responsible:	Doctoral Program in Electrical and Computer Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
PDEEC	9	Syllabus since 2007/08	1	-	7,5	70	200

Teaching language

English

Objectives

To give the first-year PhD students a broad, but simultaneously in-depth, overview of search and optimization methodologies, applicable to the resolution of multi-disciplinary decision problems, under a decision support framework.
More specifically, it is expected to endow the students with skills to:
- identify optimization problems and approach them in a structured way;
- build models for optimization problems;
- use heuristics methods to obtain solutions for the problems;
- identify the best techniques to solve a particular problem;
- implement, test and validate, search methodologies to solve different classes of optimization problems.

Program

Heuristics and Local Search
Constructive heuristics
Exhaustive search
Neighbourhood structures
Local search
Divide and Conquer and Dynamic Programming
Branch and Bound and A* Algorithms
Dealing with infeasibility in search methods
Non-populational metaheuristics
Simulated Annealing
Tabu Search
GRASP
Variable Neighbourhood Search
Populational metaheuristics
Genetic algorithms and evolutionary programming
Ant Colonies
Swarm intelligence

Mandatory literature

Michaelwicz, Zbigniew; Fogel, David B.; How to Solve It: Modern Heuristics, Springer-Verlag, 2004. ISBN: 3-540-22494-7

Complementary Bibliography

Burke, Edmund K. 340; Search Methodologies. ISBN: 978-0387-23460-1
Robert T. Clemen; Making hard decisions. ISBN: 0-534-26034-9
Edited by Colin R. Reeves; Modern heuristic techniques for combinatorial problems. ISBN: 0-07-709239-2
Powell, S., Baker, K; The Art of Modeling with Spreadsheets, wiley, 2009. ISBN: 978-0-470-39376-5
Hillier, Frederick S.; Introduction to operations research. ISBN: 007-123828-X

Teaching methods and learning activities

Classes will be mainly organized as lectures, in opposition to home work that will mainly be organized around assignments and therefore will take place in off class periods.
A strong interaction and participation of students, leading to a real active learning environment, will be sought in the lectures. In concrete the following learning strategies will be used:
- Group discussion based on scientific papers
- Small problems discussion and resolution
- Exploitation of alternative problem development paths

keywords

Physical sciences > Mathematics > Applied mathematics > Operations research
Physical sciences > Mathematics > Algorithms

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Description	Type	Time (hours)	Weight (%)	End date
Attendance (estimated)	Participação presencial	42,00
Assignments	Trabalho escrito	84,00		2012-01-20
Final Exam	Exame	3,00		2012-02-03
	Total:	-	0,00

Amount of time allocated to each course unit

Description	Type	Time (hours)	End date
Study	Estudo autónomo	74	2012-02-03
	Total:	74,00

Eligibility for exams

N/A

Calculation formula of final grade

The components for student evaluation are:
o Team work assignments (weight of 50%)
o Assessment by the colleagues (weight of 20%)
o Final exam (weight of 30%)

Each component will be graded and the final score will be calculated as the weighted average of all components.

Examinations or Special Assignments

N/A

Special assessment (TE, DA, ...)

These students will be subject to all evaluation procedures of regular students, i.e., they must deliver their assignments specified during the course plus any special works also specified plus a final exam, being the only difference towards regular students that they are not required to attend classes and deliver assignments in the same dates as regular students, in the cases the law specifically states it.

Classification improvement

N/A