Teaching Methodologies
The lectures are expository but tend to promote the active participation of students, either by asking questions, either through the resolution of exercises involving the application of the topics being exposed.In In tutorial classes the knowledge acquired in lectures is applied by resolution of practical exercises. The assessment has two components: final exam – 17 points (required a minimum of 35%); practical work – 3 points (required a minimum of 30%). It is necessary an individual study of students out of class (for better monitoring of lessons).
Learning Results
After attending this curricular unit, students must: know and understand the fundamental characteristics of the most representative optimization and decision problems; be able to translate simple optimization and decision problems into mathematical models of linear programming (LP); understand the PL algorithms and know to apply the appropriate ones to solve this kind of problems; be able to interpret the solutions obtained by the application of these algorithms to the mathematical models.
Program
Theoretical content:
1 – Introduction to Operations Research
2 – Linear Programming
3 – Introdution to Pos-Optimization and Sensitivity Analysis
4 – Goal Programming
5 – Multi-Objective Linear Programming
Tutorial content:
– Resolution of theoretical-practical exercises involving the various chapters of the theoretical program.
Internship(s)
NAO