The asymptotic probabilistic genetic algorithm


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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.

About the authors

P V Galushin

Siberian State Aerospace University named after academician M. F. Reshetnev, Russia, Krasnoyarsk

Siberian 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, Krasnoyarsk

Siberian State Aerospace University named after academician M. F. Reshetnev, Russia, Krasnoyarsk

References

  1. 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)

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Copyright (c) 2009 Galushin P.V., Semenkin E.S.

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