Decision Support Systems

Code:

CINF030

Acronym:

SAD

Keywords
Classification	Keyword
CORDIS	Social sciences

Instance: 2024/2025 - 2S

Active?	Yes
Web Page:	https://sites.google.com/g.uporto.pt/cinf-sad
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	37	Study plan	3	-	6	41	162

Teaching language

Portuguese

Objectives

Context

This course focuses on applying analytical methods to support decision-making, providing students with modeling and optimization tools essential for addressing and solving problems in organizations, both in industry and services.

Specific Objectives

This course aims to provide students with a comprehensive overview of the principles and techniques used in rational decision-making processes. It covers decision-making in contexts of risk and uncertainty, as well as situations involving multiple criteria, considering both quantitative and qualitative aspects.

Learning outcomes and competences

Equip students with the skills to:

• Identify and systematically approach decision-making problems;
• Develop decision problem models;
• Identify and apply analytical methods to obtain solutions for the developed models, supporting well-founded decisions;
• Use spreadsheets for analysis and solution generation for the developed models;
• Formulate decision problems with multiple criteria and apply decision support methodologies in environments of uncertainty and risk.

Working method

Presencial

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

It is recommended that students have basic knowledge of spreadsheets, including the use of functions, data manipulation, and table creation. Additionally, fundamental computing skills, such as file organization and the use of software for data analysis, are beneficial.

Program

• Formulating linear programming problems with continuous variables: mathematical modeling, interpretation of optimal solutions, and analysis of practical cases.


• Formulation of network problems using linear programming models: representation of problems in graphs, including flow problems, shortest paths, and minimum spanning trees.


• Formulation of linear programming problems with integer and binary variables: modeling and solving combinatorial problems, including logical and capacity constraints.


• Use of Excel Solver and sensitivity report analysis: implementation of optimization models in Excel, interpretation of sensitivity reports, and evaluation of parameter variations.


• Decision Theory: fundamentals of decision-making, including decision criteria under certainty, risk, and uncertainty, and the construction and analysis of decision trees.


• Multicriteria Decision Problems: formulation and resolution of decision problems with multiple criteria, approaches such as goal programming, and multicriteria decision support methods.

Mandatory literature

Docentes de SAD; Documentação de apoio preparada pelos docentes da unidade curricular (Available at the course site)

Complementary Bibliography

Powell, Stepehn G.; Management Science. ISBN: 978-0-470-03840-6
Clemen, Robert T.; Making hard decisions with decision tools, N. ISBN: 0-534-36597-3

Teaching methods and learning activities

The presentation of the course topics will be complemented, whenever possible, with active learning methods, encouraging student participation. Concepts will be illustrated through practical cases, examples, and real-world problems to enhance understanding and application.

Classes will include moments of discussion and reflection, encouraging students to analyze the presented problems and explore different solution approaches critically. Practical exercises will be provided to consolidate acquired knowledge, with continuous feedback from the instructor.

Additionally, support materials such as lecture notes, bibliographic references, and tutorials on modeling and optimization tools will be made available. Doubt clarification will be encouraged during classes. Students will be encouraged to use appropriate software to solve the problems addressed throughout the course.

Software

Microsoft Excel

keywords

Physical sciences > Mathematics > Applied mathematics > Operations research
Social sciences > Economics > Management studies > Industrial management

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Teste	75,00
Trabalho prático ou de projeto	25,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	121,00
Frequência das aulas	41,00
Total:	162,00

Eligibility for exams

To obtain attendance in this course, students must achieve a minimum of 20% of 12 points in the continuous assessment component.

In addition to this requirement, students must comply with the provisions in the FEUP general assessment regulations (in Portuguese) available at FEUP General Assessment Regulations.

Calculation formula of final grade

• In-class micro-tests (closed book) (0 to 10 points): The final score will be the sum of the scores obtained in the micro-tests conducted at the end of each class, excluding the two lowest scores. Each exercise will be graded on a scale from 0 to 100%.


• Mid-term test (closed book) (0 to 5 points): The mid-term test will be graded on a scale from 0 to 100%.


• Group assignment (0 to 5 points): The group assignment will be graded on a scale from 0 to 100%.

Students will pass if their final grade is equal to or greater than 10 points.

Examinations or Special Assignments

Students not required to attend classes and who have not participated in the continuous assessment must take a comprehensive, closed-book exam during the resit period.

The group assignment component, as it cannot be evaluated in a single instance, must be completed in collaboration with the group throughout the semester.

Special assessment (TE, DA, ...)

Assessments during the special exam period will be conducted through a comprehensive closed-book exam, which will replace the continuous assessment components (micro-tests and mid-term test).

Classification improvement

Resit Period

During the resit period, students will have the opportunity to improve their grades from the continuous assessment (micro-tests and mid-term test). The highest grade between the regular period and the resit period will always be considered. All exams will be closed-book.