Computational Methods for Optimization
Objectives
1. Knowing the concept of optimization
2. Mastering the most known computational intelligence algorithms for optimization
3. Mastering the simplest operational research algorithms for optimization
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
No mandatory requirement
Bibliography
Teaching method
Both theoretical and practical classes are organized using white board, slides and programming using a
well-known programming environment.
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. Linear programming
8. Graphical method to solve linear programming problems
9. Simplex
10. Hints to non-linear programming