Genetic algorithms (PM)
Type: For the student's choice
Department: computational mathematics
Lectures
| Semester | Amount of hours | Lecturer | Group(s) |
| 8 | 42 | Borachok I. V. |
Laboratory works
| Semester | Amount of hours | Group | Teacher(s) |
| 8 | 28 | PMp-41 | Borachok I. V., A. V. Beshley |
Course description
The theory and practical application of various genetic algorithms and genetic programming are considered. Students will gain an understanding of the processes of evolution, mechanisms of selection, recombination, and mutation, and learn to apply these ideas to solving complex optimization problems. The course includes theoretical foundations and practical exercises using GNU Octave.
Recommended Literature
- Goldberg D.E. Genetic Algorithm in Search, Optimisation and Machine Learning / D.E. Goldberg // Addison-Wesley, Reading, MA. 1989.
- Koza J.R. Genetic programming as a means for programming computers by natural selection / J.R. Koza // Stat Comput 4, 87–112. 1994.
- Michalewicz Z. Genetic Algorithms + Data Structures = Evolution Programs, 3rd ed. / Z. Michalewicz // Springer-Verlag, Berlin. 1996.
- Mitchell M. An introduction to genetic algorithm / M. Mitchell // The MIT Press. 1998.
- Vanneschi L. Genetic Programming. In: Lectures on Intelligent Systems / L. Vanneschi, S. Silva // Natural Computing Series. Springer, Cham. 2023.