Decision Support Systems

Code:

EEC0086

Acronym:

SADE

Keywords
Classification	Keyword
OFICIAL	Other Technical Areas

Instance: 2010/2011 - 2S

Active?	Yes
Web Page:	https://www.fe.up.pt/si/disciplinas_GERAL.FormView?P_ANO_LECTIVO=2008/2009&P_CAD_CODIGO=EEC0086&P_PERIODO=2S
Responsible unit:	Department of Industrial Engineering and Management
Course/CS Responsible:	Master in Electrical and Computers Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIEEC	113	Syllabus (Transition) since 2010/2011	4	-	6	63	162
			5
		Syllabus	4	-	6	63	162
			5

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
ed by Jonathan Rosenhead & John Mingers; Rational analysis for a problematic world revisited. ISBN: 0-471-49523-9

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	56,00
Final Exam	Exame	2,00
Group work, reports and presentations	Trabalho laboratorial	36,00		2011-06-10
	Total:	-	0,00

Amount of time allocated to each course unit

Description	Type	Time (hours)	End date
Distributed study	Estudo autónomo	50	2011-06-10
Preparation for the Final Exam	Estudo autónomo	16	2011-06-10
	Total:	66,00

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.