Non-stationary optimization with multi-population evolutionary algorithm

• Autorzy: Stańczak J. , Trojanowski K.
• Konferencja: Evolutionary Computation and Global Optimization (10; Krajowa Konferencja Algorytmy Ewolucyjne i Optymalizacja Globalna; 11-13.06.2007; Będlewo, Poland)
• Języki publikacji: EN

Abstrakty

EN

Non-stationary optimization of randomly changing environments is a subject of unfading interest.In this paper we study application of multipopulation evolutionary algorithm to this problem. Presented algorithm works with a set of sub-populations managed by the mechanism of exclusion coming from the multiswarm version of particle swarm approach. The results show significant improvement of the efficiency of the new algorithm in comparison with a single population approach.

Słowa kluczowe

EN

evolutionary algorithm; optimisation

• Wydawca: Oficyna Wydawnicza Politechniki Warszawskiej
• Czasopismo: Prace Naukowe Politechniki Warszawskiej. Elektronika
• Rocznik: 2007
• Tom: z. 160
• Strony: 251--259
• Opis fizyczny: Bibliogr. 15 poz., schem.

Twórcy

autor

Stańczak J.

autor

Trojanowski K.

• Systems Research Institute Polish Academy of Science Warsaw,

Bibliografia

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• [10] J. Mulawka, J. Stańczak, and B.K. Verma. Genetic algorithms with adaptive probabilities of operators selection. In Third Int'nal Conf. on Computational Intelligence and Multimedia Applications (ICCIMA'99), pages 464-468. IEEE Computer Society, 1999.
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• [13] J. Stańczak and K. Trojanowski. Properties of selection methods applied to nonstationary optimization tasks. In Proc. of the 7th National Conf. on Evolutionary Computation and Global Optimisation, pages 171-180. Warsaw Univ. of Technology Publishing House, 2004.
• [14] K. Trojanowski. B-cell algorithm as a parallel approach to optimization of moving peaks benchmark tasks. Accepted for publication at the Int'nal Conf.: 6-th Computer Information Systems and Industrial Management Applications, CISIM 2007, Ełk, Poland, June 28 - June 30, 2007.
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