The paper gives a description of the combined algorithm multiarnative
optimization and method of particle swarm. As topology neighborhood the
cluster topology is adopted. The structural scheme of the combined algorithm
multialternative optimization and method of particle swarm is given.
1. Lvovich Ya.E. Multi-alternative optimization: theory and applications.
Voronezh: Quarta Publishing House, 2006.
2. I.E. Lvovich, S.V. Andrahanov Integration of Procedures
multi-alternative optimization and particle swarm method / Bulletin
Voronezh State Technical University. 2010.V. 6.
No. 12. S. 29-31.
3. S. I. Kiselev and others. The solution of numerical problems of automation on a PC.
SPbSTU, SPb, 1993.
4. Modeling of robotic systems and flexible automated production. Book 5 of the series “Robotics and flexible automated production”. Ed. THEM. Makarova. M.: Higher
School, 1986.
5. J. Kennedy and R. Eberhart, “Particle swarm optimization,”
in the Proceedings of IEEE International Conference on Neural Networks,
Perth, Australia, Vol. 4, pp. 1942-1948, 1995.
6. Kennedy, J., Eberhart, R.C., and Shi, Y., Swarm Intelligence.
Morgan Kaufmann, 2001.
7. Li Liu, Wenxin Liu, David A. Cartes, “Particle swarm optimization-based
parameter identification applied to permanent magnet synchronous motors”,
Engineering Applications of Artificial Intelligence, Volume 21, Issue 7,
October 2008, Pages 1092-1100.
8. Pant, M., Thangaraj, R. and Abraham, A., (2008), "Particle Swarm
Optimization Using Adaptive Mutation", IEEE/DEXA'08, pp. 519-523.
Andrakhanov Sergey Valeryevich
Email: app@vivt.ru
Voronezh Institute of High Technologies
Voronezh, Russian Federation
