Métodos Computacionais para Optimização
Objectives
Introduction of the most known optimization algorithms from operational research and computational intelligence
General characterization
Code
100146
Credits
4.0
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
Presence in the classes will not be counted and will not have a weight in the final grade.
Final grade is a weighted average between a project and the final exam.
Bibliography
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
Teaching method
Theoretical classes - slides
Practical classes - slides and coding exercises
Evaluation method
- Exam
- Final Project
- Presence in class
Subject matter
- Introduction to optimization. Definition and concepts.
- Introuction to Operative Research
- Linear Programming - graphical method
- Simplex
- No Free Lunch Theorem
- Heuristic Methods
- Fitness Landscapes
- Hill Climbing
- Simulated Annealing
- Genetic Algorithms
- Particle Swarm Optimization