Computational Intelligence for Optimization
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.
Weekly - Available soon
Total - Available soon
Portuguese. If there are Erasmus students, classes will be taught in English
¿Simulated Annealing and Boltzmann Machines¿, E. Aarts and J. Korst, John Wiley and Sons; ¿Genetic Algorithms in Search, Optimization and Machine Learning¿, D. E. Goldberg, Addison-Wesley; 0; 0; 0
(Black)board and slides for theoretical classes, projection of a programming environment for software development in the practical classes.
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.
- 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: