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Unconvencional Optimization Methods

Type of study Doctoral
Language of instruction Czech
Code 342-0958/01
Abbreviation NMO
Course title Unconvencional Optimization Methods
Credits 10
Coordinating department Institute of Transport
Course coordinator doc. Ing. Dušan Teichmann, Ph.D.

Subject syllabus

1. Stochastic optimization methods based on Simulated Annealing and Tabu Search Strategies.
2. Swarm optimization algorithms and methods (PSO, ACO, GSO, FSO, BCO, BA, ABC, HBMO).
3. Optimization Problems Solving under uncertainty.
4. Advanced genetic algorithms.
5. Artifical neural networks.
6. Max-plus algebra.
7. Wawelets and its using for optimization methods.
8. Voronoi diagrams.
9. Cluster Analysis.

Literature

AFFENZELLER, M.; WAGNER, S.; WINKLER, S.; BEHAM, A.: Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications. London: Chapman and Hall / CRC, 2018. ISBN 978-11-381-1427-2 
SIMON, D.: Evolutionary Optimization Algorithms. New York: John Wiley&Sons, 2013. ISBN 978-04-709-3741-9
Články publikované ve vědeckých časopisech (aktuální seznam publikací obdrží doktorand před zahájením výuky).

Advised literature

HASSOUN, M., H.: Fundamentals of Artifical Neural Networks. Bradford Book, 2003. ISBN 978-02-625-1467-5 
IBA, H.; NOMAN, N.: New Frontier in Evolutionary Algorithms: Theory and Applications. London: Imperial College Pr, 2011. ISBN 978-18-481-6681-3 
MAN, K., F.; TANG, K., S., KWONG, S.: Genetic Algorithms - Concepts and Designs. London: Springer, 1999. ISBN 978-1-4471-0577-0 


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