The objective of this curricular unit is to develop decision-making competencies applied to the industrial and service context. It is intended to teach how to structure a problem so as to choose the appropriate methods to support them in decision making, as well as how to apply the methods and analyze the results. Problems will be addressed in a deterministic context, with a single decision criterion as well as considering several decision criteria. To deal with contexts of uncertainty, different methods of decision-making will be taught, with different levels of complexity,
Students should also develop teamwork skills to understand, formulate and solve problems in a real context, as well as develop oral and written communication skills to describe problems, their approach to support the decision-making process, and justification of options.
António Carlos Bárbara Grilo, Pedro Emanuel Botelho Espadinha da Cruz
Weekly - 2
Total - 36
Students should have basic knowledge of Linear programming.
All content (theory and exercises are on the UC website at www.unidemi.com/models.
Additional content can be found in the following books:
1) Applied Management Science: Modeling, Spreadsheet Analysis, and Communication for Decision Making,2nd Edition,
John A. Lawrence, Barry A. Pasternack, ISBN: 978-0-471-39190-6, February 2002
2) Management Decision Making: Spreadsheet Modeling, Analysis, and Application
George E. Monahan
ISBN 10: 0521781183 ISBN 13: 9780521781183
Publisher: Cambridge University Press, 2000
· Discussion of case studies with students;
· Problem solving sessions;
· Team work;
· Presentation and discussion of team works;
The final assessment of the curricular unit (UC) of Decision Models (MDc) will be based on the following elements:
- 1 Test (T1), with 50% weight in the final assessment
- 1 Group Work (TG). It consists of the development of a work to be carried out as specified. Groups will have a maximum of 5 students.
The final MDc grade will be composed as follows:
Final grade = 0.50*T + 0.50*TG
T - test score;
TG - group work note
The score for each of the assessment components is rounded to the nearest tenth.
To be approved at the UC, students must obtain frequency at the UC through a positive grade (>=9.5 values) in the group work. Approval occurs if the Final Grade is equal to or greater than 9.5 values in both evaluation elements.
If a student has not passed the global test, if he/she has attended the current year or the previous year, he/she may take the appeal exam. The final grade will be calculated by the same formula, replacing the test grade with the exam grade.
1. Introduction to how we make decisions. Phases of the decision process. Type of decision-making environments: certainty, risk and uncertainty.
2. Deterministic decision models. Selection and evaluation of alternatives. Formulation and development of the model. Models based on linear programming. Sensitivity analysis. Analysis of large variations.
3. Decision criteria in uncertainty. Value of information. Decision criteria with risk.
4. Decision trees. Nodes, alternatives and states. Selection, qualification and valuation of alternatives. Bayesian analysis in the estimation of probabilities. Value of Perfect and Imperfect Information.
5. Value Functions. Utility, indifference and risk. Risk premium.
6. Decision-making with multiple criteria. The AHP method. The TOPSIS method. Multi-Objective Methods.
7. Monte Carlo simulation. Applications in the Evaluation of Investment Projects.
Programs where the course is taught: