Computational Intelligence for Optimization
Objectives
1. Knowing the concept of optimization
2. Mastering the most known computational intelligence algorithms for optimization
General characterization
Code
200142
Credits
7.5
Responsible teacher
Leonardo Vanneschi
Hours
Weekly - Available soon
Total - Available soon
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Prerequisites
No mandatory requirement
Bibliography
- Simulated Annealing and Boltzmann Machines?, E. Aarts and J. Korst
- Genetic Algorithms in Search, Optimization and Machine Learning, D. E. Goldberg
Teaching method
Tanto as aulas teóricas quanto as práticas são organizadas com quadro branco, slides e programação usando um
ambiente de programação bem conhecido.
Evaluation method
Project: 30%
Final exam: 70%
Subject matter
1. Optimization Problems - Introduction and definitions
2. No Free Lunch Theorem
3. Hill Cimbing
4. Fitness Landscapes
5. Simulated Annealing
6. Genetic Algorithms
7. Genetic Programming
Programs
Programs where the course is taught: