Operations Research

Base Knowledge

Basic knowledge of Linear Algebra is recommended.

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 Theoretical-practical and practical classes the knowledge acquired in lectures is applied by resolution of theoretical-practical exercises / programs implementation in MatLab.

Learning Results

After attending this course, students must:
1 – Be able to translate simple optimization and decision problems into mathematical models of linear programming (LP);
2 – Understand the PL algorithms and know to apply the appropriate ones to solve this kind of problems;
3 – Be able to interpret the solutions obtained by the application of these algorithms to the mathematical models;
4 – Be able to computationally implement PL algorithms.


Theoretical content:
1 – Introduction to operations research
2 – The linear programming (LP) model
Examples of linear programming problems
Formulating the mathematical model
Graphical representation
Particular cases
3 – The Simplex method
Introductory concepts
Algorithm of the method in the tabular form
The “Big M” and “Two Phases” methods
Particular cases of the Simplex method
4 – Duality and the dual Simplex method
The dual problem
Fundamental properties of duality
The dual Simplex method
5 – Particular problems of linear programming
The problem of transportation

Theoretical-practical/practical content:
– Resolution of theoretical-practical exercises involving the various chapters of the theoretical program
– Computational implementation of PL algorithms using MatLab

Curricular Unit Teachers