Decision Support Systems

Code:

CINF030

Acronym:

SAD

Instance: 2014/2015 - 2S

Active?	Yes
Responsible unit:	Department of Industrial Engineering and Management
Course/CS Responsible:	Bachelor of Arts in Information Science

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
CINF	35	Plano Oficial a partir de 2008/2009	3	-	6	56	162

Teaching language

Portuguese

Objectives

The main objective of this course is to convey students a global vision about the principles and techniques used in rational decision-making processes with multiple criteria and risk and uncertainty situations, stressing in particular the role of quantitative methods and qualitative issues.

Learning outcomes and competences

At the end of this course students should be able to:
- Understand the complexity as well as the quantitative and qualitative features of the decision-making process and apply simple approaches to problem structuring and problem solving;
- Use optimization models and algorithms as well as heuristic techniques in solving problems of practical interest;
- Formulate multi-criteria decision problems and apply adequate decision support methodologies in uncertain environments;
- Develop and implement programs tender selection methods suitable.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Basic skills on spredsheets (Informática Básica).

Program

1. Decision Support Systems: General structure and components; Operational Research Methodology; Quantitative and qualitative decision-making methods; Structuring decision-making problems.
2. Optimization: Linear and integer programming models; Transportation and assignment problems; Introduction to combinatorial optimization – models and applications; Heuristic approaches.
3. Decision theory, multi-criteria and multi-objective decision support: Decisions with uncertainty or risk; Decision criteria; Classical Decision Theory – decision trees, utility functions and value functions; Analytic Hierarchy Process (AHP).
4. Public tenders: methodological features, procedures, selection and evaluation methods.

Mandatory literature

Maria Antónia Carravilla, José Fernando Oliveira; Documentação de apoio a Investigação Operacional, 2012
Manuel Matos; Ajuda Multicritério à Decisão - introdução, 2005

Complementary Bibliography

Powell, Stepehn G.; Management Science. ISBN: 978-0-470-03840-6
Cândida Mourão, Leonor Santiago Pinto, Margarida Vaz Pato, Onofre Simões, Jorge Miguel Silva Valente; Investigação Operacional, Verlag Dashöfer Edições Profissionais, 2011. ISBN: 978-989-642-184-7
Clemen, Robert T.; Making hard decisions with decision tools, N. ISBN: 0-534-36597-3

Teaching methods and learning activities

The methods and techniques are introduced in lecture classes systematically using practical examples and case studies. The learning process is complemented with problem solving sessions supported by computer software (spreadsheets) in tutorial classes. The learning process is completed with evaluation quizzes and teamwork assignments

Software

Microsoft Excel

keywords

Physical sciences > Mathematics > Applied mathematics > Operations research

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	60,00
Participação presencial	0,00
Teste	20,00
Trabalho escrito	20,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Elaboração de relatório/dissertação/tese	10,00
Estudo autónomo	56,00
Frequência das aulas	56,00
Trabalho laboratorial	40,00
Total:	162,00

Eligibility for exams

Admission criteria set according to General Evaluation Rules.

Calculation formula of final grade

The final mark (CF) will be computed by the following formula:
            CF = 0.20 FA + 0.20 TG + 0.60 EF
FA – individual quizzes:
- 6 quizzes (tutorial classes);
- average of the best 4 marks achieved by each student.
TG – Teamwork assignments:
- 2 small size teamwork assignments;
- average of the 2 marks achieved by each student.
EF – Final Exam:
- open book exam.

To pass this course, apart from a final grade no less than 10, is required a minimum grade of 7 in the final exam.

Special assessment (TE, DA, ...)

Special evaluations will be made by a final exam.

Classification improvement

Students may choose between:
- improving the components Quizzes (FA) and Final Exam (EF);
- improving only the component Final Exam (EF).

The component teamwork assignments (TG) is not possible to improve.