Inteligência Computacional para Otimização
Objetivos
No requirement
Caracterização geral
Código
200142
Créditos
7.5
Professor responsável
Mauro Castelli
Horas
Semanais - A disponibilizar brevemente
Totais - A disponibilizar brevemente
Idioma de ensino
Português. No caso de existirem alunos de Erasmus, as aulas serão leccionadas em Inglês
Pré-requisitos
- 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
- Genetic Programming
Bibliografia
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
Método de ensino
First epoch: weighted average between an intermediate test and a project.
Second epoch: weighted average between a final exam and a project (the same of the first epoch).
Método de avaliação
English
Conteúdo
(White)board and slides for theoretical classes, projection of a programming environment for software development in the practical classes.
Cursos
Cursos onde a unidade curricular é leccionada: