Computational Intelligence for Optimization
Code
200142
Academic unit
NOVA Information Management School
Credits
7.5
Teacher in charge
Leonardo Vanneschi
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Objectives
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.
Prerequisites
No requirement
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
Bibliography
¿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
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.