Decision Support Systems
Keywords |
Classification |
Keyword |
OFICIAL |
Other Technical Areas |
Instance: 2009/2010 - 2S
Cycles of Study/Courses
Acronym |
No. of Students |
Study Plan |
Curricular Years |
Credits UCN |
Credits ECTS |
Contact hours |
Total Time |
MIEEC |
77 |
Syllabus since 2007/2008 |
4 |
- |
6 |
63 |
160 |
Teaching language
Portuguese
Objectives
In this course unit will be presented the general philosophy, structure and components of Decision Support Systems (DSS), as well as the methodologies and techniques which make students able to design and implement DSSs.
Students should be capable of understanding the complexity and aspects of decision making, as well as using techniques of problem structure and multi-criteria approaches.
Students should also familiar themselves with models and applications of Combinatorial Optimization and general heuristic techniques to solve practical problems, particularly in the domain of operation management.
Examples of DSSs will be presented and discussed. Special emphasis will be given to the aspects related to user interfaces and visual interactive simulation systems.
Program
1. Decision Support Systems (DSS): general structure and components; Quantitative methods for decision making; Operations Research methodology; Models; Qualitative aspects in decision making; Structure of decision problems
2. Theory of decision and Multi-criteria analysis; Situations of uncertainty and risk; Alternatives and decision criteria; Decision trees; Multiple-criteria decision problems; Analytic Hierarchy Process (AHP).
3. Models and modelling; Modelling in a context of problem solving; Engineering spreadsheets: spreadsheet design, development and test.
4. Spreadsheet analysis; base case analysis; what if analysis: data sensitivity, tornado diagrams; Breakeven analysis; Optimization analysis; Risk analysis
5. Operation management and Combinatorial Optimization problems: models and applications; Metaheuristic: local search algorithms, simulated annealing, taboo search; Genetic Algorithms: integration in SDDs
6. Monte Carlo simulation; Base model and sensitivity analysis; Selection of stochastic parameters; Selection of probability distributions; Selection of results; Results precision; Analysis of results of Monte Carlo simulation: frequency tables and histograms; statistics and percentiles; box diagrams
7. Simulation optimization; Simulation sensitivity analysis; Grid search; Optimization of Monte Carlo simulation models; Inclusion of simulation in models of linear optimization with stochastic objective functions and probabilistic restrictions.
8. Methodologies to design DSSs and tools to implement them; Modularity and prototyping; Organisational aspects in DSS design; Presentation and discussion of case studies.
Mandatory literature
Powell, Stepehn G.;
Management Science. ISBN: 978-0-470-03840-6
Complementary Bibliography
Turban, Efraim;
Decision support systems and intelligent systems. ISBN: 0-13-781675-8
Reeves, Colin R. 340;
Modern heuristic techniques for combinatorial problems. ISBN: 0-07-709239-2
Hillier, Frederick S.;
Introduction to operations research. ISBN: 0-07-118163-6
Teaching methods and learning activities
This course unit will be based on the presentation of program, presentation and discussion of case studies and problem solving. Classes will take place twice a week and will last 2 hours.
Students have to write reports as a part of their assessment. They will be mostly written outside class time.
Evaluation Type
Distributed evaluation with final exam
Assessment Components
Description |
Type |
Time (hours) |
Weight (%) |
End date |
Attendance (estimated) |
Participação presencial |
60,00 |
|
|
|
Exame |
3,00 |
|
|
|
Trabalho escrito |
12,00 |
|
|
|
Trabalho escrito |
12,00 |
|
|
|
Total: |
- |
0,00 |
|
Amount of time allocated to each course unit
Description |
Type |
Time (hours) |
End date |
|
Estudo autónomo |
75 |
|
|
Total: |
75,00 |
|
Eligibility for exams
See Article 4 of General Evaluation Rules of FEUP.
Calculation formula of final grade
FE (Closed book final exam) - from 0 to 20 (minimum grade: 7.5)
A1 (Practical Assignment 1) - from 0 to 20 (minimum grade: 7.5)
A2 (Practical Assignment 2) - from 0 to 20 (minimum grade: 7.5)
Final Grade
0.60 FE + 0.20 A1 + 0.20 A2
Examinations or Special Assignments
2 practical assignments (A1 and A2): groups of 3 or 4 students
- A1 (Practical Assignment 1)- about theme 3 and 4
- A2 (Practical Assignment 2)- about theme 5 and 8
Date of delivery will be set. Students may be asked to give a presentation and discuss their assignments.
Special assessment (TE, DA, ...)
As for regular students.
Classification improvement
Students cannot improve the grade of their practical assignments.