Métodos Computacionais para Optimização
Objectivos
The discipline has the objective of teaching the basis of optimization, and some of the most well-known and widely used computational methods for effectively and efficiently solving optimization problems. More particularly, two types of strategies will be studied: the ones belonging to the field of Operational Research and the ones belonging to the field of Computational Intelligence.
Caracterização geral
Código
100146
Créditos
4.0
Professor responsável
Leonardo Vanneschi
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
Presence in the classes will be counted and will have a weight in the final grade
Bibliografia
Recommended Bibliography
Operational Research:
¿Operations Research, Applications and Algorithms¿, W. Winston.
¿Introduction to Operations Research¿, F. Hillier and G. Lieberman.
Computational Intelligence:
¿Simulated Annealing and Boltzmann Machines¿, E. Aarts and J. Korst
¿Genetic Algorithms in Search, Optimization and Machine Learning¿, D. E. Goldberg
Método de ensino
Theoretical classes - slides and use of (black-)board
Practical classes - slides, use of (black-)board and coding exercises
Método de avaliação
- Exam (60%)
- Project (40%)
Conteúdo
- Introduction to optimization. Definition and concepts.
- No Free Lunch Theorem
- Operational Research
- Linear Programming
- Simplex
- Non-linear programming (hints)
- Computational Intelligence
- Heuristic Methods
- Fitness Landscapes
- Hill Climbing
- Simulated Annealing
- Genetic Algorithms
- Particle Swarm Optimization