Guarantee:
Doc. RNDr.
Aims of the
subject: To introduce our students into the dynamically growing
area of softcomputing that is composed by evolutionary algorithms. Besides the
theoretical concepts and description of fundamental principles of evolutionary
computing, the close attention will be paid to various application
opportunities of these algorithms when solving hard problems.
Requirements
on students:
Written assignment preferably focused on the relationship
between evolutionary algorithms and the subject of student’s dissertation. The
specific topic for each student will be discussed with the lecturer.
Subject
matter:
1.
Fundamentals of evolutionary
algorithms – from
2.
Genetic algorithms
2.1.
Representation of individuals
2.2.
Selection mechanisms
2.3.
Genetic operators
2.4.
Reproduction strategies
2.5.
Theoretical background
3.
Hybrid genetic algorithms
4.
Application of genetic algorithms
4.1.
Combinatorial optimisation
4.2.
Multicriteria optimisation
4.3.
Scheduling problems
4.4.
Transportation and distribution
problems
5.
Genetic programming and its
applications
Assessment
strategy and method: Written examination.
Indicative
reading:
[1]
Banzhaf, W., Nordin, P., Keller,
R.E., Francone, F.D.: Genetic Programming. An Introduction. On the Automatic
Evolution of Computer Programs and Its Applications.
[2]
Coley, A.D.: An Introduction to
Genetic Algorithms for Scientist and Engineers. World Scientific,
[3]
Eiben, A.E., Smith, J.E.: Introduction to Evolutionary Computing.
[4]
Gen, M., Cheng, R.: Genetic
Algorithms&Engineering Optimization. John Wiley&Sons, Chichester
2000.
[5]
Gottlieb, J.: Evolutionary
Algorithms for Constrained Optimization Problems. Shaker Verlag,
[6]
Hromkovič, J.: Algorithmics for
Hard Problems (2nd Edition).
[7]
Koza, J. R.: Genetic Programming.
On the Programming of Computers by Means of Natural Selection.
[8]
Koza, J. R.: Genetic Programming
II. Automatic Discovery of Reusable Programs.
[9]
Lažanský, J.: Evoluční výpočetní
techniky. In Mařík V., Štěpánková O., Lažanský J. a kol.:
Umělá inteligence 3. Academia, Praha 2001, s. 117-160.
[10]
Michalewicz, Z., Fogel, B.D.: How to Solve
It: Modern Heuristics.