The asymptotic probabilistic genetic algorithm
- Authors: Galushin PV1, Semenkin ES1
-
Affiliations:
- Siberian State Aerospace University named after academician M. F. Reshetnev, Russia, Krasnoyarsk
- Issue: Vol 10, No 5 (2009)
- Pages: 45-49
- Section: Articles
- URL: https://journals.eco-vector.com/2712-8970/article/view/508554
- ID: 508554
Cite item
Full Text
Abstract
This paper proposes the modification of probabilistic genetic algorithm, which uses genetic operators, not affecting the particular solutions, but the probabilities distribution of solution vector's components. This paper also compares the reliability and efficiency of the base algorithm and proposed modification using the set of test optimization problems and bank loan portfolio problem.
Keywords
About the authors
P V Galushin
Siberian State Aerospace University named after academician M. F. Reshetnev, Russia, KrasnoyarskSiberian State Aerospace University named after academician M. F. Reshetnev, Russia, Krasnoyarsk
E S Semenkin
Siberian State Aerospace University named after academician M. F. Reshetnev, Russia, KrasnoyarskSiberian State Aerospace University named after academician M. F. Reshetnev, Russia, Krasnoyarsk
References
- Semenkin, E. S. Probabilistic evolutionary algorithms of complex systems optimization/E. S. Semenkin, E. A. Sopov // Proc. of Int. Conf. Intelligent systems (AIS'05) and Intelligent CAD (CAD-2005): in 3 vol. Vol. 1. M.: Fizmatlit, 2005. (inRussian)