Inteligência Computacional para Otimização


This course should introduce students to the basic concept of optimization and to a set of heuristic methods for solving, or approxumating, optimization problems. At the same time, this discipline should help students acquiring some bases of programming.

General characterization





Responsible teacher

Mauro Castelli


Weekly - Available soon

Total - Available soon

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English


No requirement


Aarts, Emile, ; Korst, Jan (1989). Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing. Chichester : Wiley, 1989. xii, 272 p. . ISBN 0-471-92146-7

Goldberg, David, - Genetic algorithms in search, optimization and machine learning. Boston : Addison-Wesley, 1989. xiii, 412 p. . ISBN 978-0-201-15767-3

Teaching method

(Black)board and slides for theoretical classes, projection of a programming environment for software development in the practical classes.

Evaluation method

First epoch: weighted average between the average grade obtained in a set of evaluations along the semester and the final test.
Second epoch: final test.

Subject matter

- Motivations of the course
- Optimization Problems
- Fitness Landscapes
- Hill Climbing
- Simulated Annealing
- Hints to Tabu Search
- Genetic Algorithms
- Advanced Genetic Algorithms methods
- Hints to Particle Swarm Optimization


Programs where the course is taught: