scientific edition of Bauman MSTU
SCIENCE & EDUCATION
Bauman Moscow State Technical University. El № FS 77 - 48211. ISSN 1994-0408
# 04, April 2010
List of literature
1. Mostaghim S., Teich, J. Strategies for Finding Good Local Guides in Multi-Objective Particle Swarm Optimization (MOPSO) // Swarm Intelligence Symposium: Proceeding, 2003. - pp. 26–33.
2. Karpenko A.P., Seliverstov E.Yu. Global'naya optimizaciya metodom roya chastic. Obzor // Informacionnye tehnologii, 2010, ╧ 2, c. 25-34.
3. Subbotin S.A., Oleinik An.A., Oleinik Al.A. PSO-metod, «Intellektual'nye mul'tiagentnye metody (Swarm Intelligence)», ╧3, 2006, s. 55-70.
4. Karpenko A.P. Metody optimizacii [Elektronnyi resurs].- (http://bigor.bmstu.ru).
5. Hu X., Eberhart R. Multiobjective optimization using dynamic neighborhood particle swarm optimization // World Congress on Computational Inelligence: Proceeding, 2002.- pp. 1677–1681.
Publications with keywords: multiobjective optimization, Pareto set, Method of a plenty of particles, PSO method
Publications with words: multiobjective optimization, Pareto set, Method of a plenty of particles, PSO method
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