Detail předmětu

Evolution Algorithms

FEKT-NEALAk. rok: 2019/2020

The course is focused on deterministic and stochastic optimization methods for finding global minima. It focuses on evolutionary algorithms with populations such as genetic algorithms, controlled random search, evolutionary strategies, particle swarm method, the method of ant colonies and more.

Prerekvizity

Jsou požadovány znalosti na úrovni bakalářského studia a platné přezkoušení pro kvalifikaci pracovníků pro samostatnou činnost (ve smyslu §6 Vyhlášky 50).

Doporučená nebo povinná literatura

Haupt, R.L., Haupt, S.E.: Practical Genetic Algorithms. John Wiley & Sons, New Jersey, 2004 (EN)

Způsob a kritéria hodnocení

Requirements for completion of a course are specified by a regulation issued by the lecturer responsible for the course and updated for every year.
- 30 points can be obtained for activity in the laboratory exercises, consisting in solving tasks (for the procedure for the examination must be obtained at least 15 points)
- 70 points can be obtained for the written exam (the written examination is necessary to obtain at least 35 points)

Jazyk výuky

angličtina

Osnovy výuky

1. Optimization based on mathematical analysis, optimality conditions, gradient, Hessian
2. Method of steepest descent, Newton's method
3. Stochastic algorithms for finding global minima, the simplex method
4. Evolutionary algorithms with populations. Binary genetic algorithms.
5. Continuous genetic algorithms.
6. Controlled random search, evolutionary strategies, particle swarm
7. Differential evolution, SOMA, ant colony
8. Swarm algothms: BAT, FA, GSO.
9. Swarm algothms: GWO, BA, ABC.
10. Test function for checking optimization algorithms
11. Experimental comparison of evolutionary algorithms
12. Introduction to genetic programming

Cíl

Obtaining an understanding about deterministic and stochastic optimization methods. Introduction to the evolutionary algorithms with populations for finding the global extremes multidimensional functions. Introduction to the genetic programming.

Zařazení předmětu ve studijních plánech

  • Program EEKR-MN magisterský navazující

    obor MN-BEI , 2. ročník, zimní semestr, 5 kreditů, volitelný oborový

Typ (způsob) výuky

 

Přednáška

26 hod., nepovinná

Vyučující / Lektor

Cvičení na počítači

13 hod., povinná

Vyučující / Lektor

Ostatní aktivity

13 hod., povinná

Vyučující / Lektor