Topology effect of two PSO and simplex hybrids
Keywords:
optimization, particle swarm optimization, simplex, hybridsAbstract
This paper shows optimization results for a group of standard functions. When the optimization algorithm PSO is hybridized with the simplex traditional algorithm (SX, Nelder-Mead) in two different ways, i. e. thealternating interaction hybrid (PSOSX(AIH)) and the parametric evolution hybrid (PSOSX(PEH)), markedly noticeable effects are observed in both the computing time and the accuracy and precision of their results during the optimization process.
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F. Chan, M. Kumar. “Swarm intelligence”. Focus on ant and particle swarm optimization. Ed. I-Tech Education and Publishing. Vienna. Chap. 7. 2007. pp. 111-139.
F. Van den Berg. An analysis of particle swarm optimizers. Ph.D. Thesis. University of Pretoria. Pretoria. 2002. pp. 1-135.
A. Moraglio, C. Di Chio, J. Togelius, R. Poli. “Geometric Particle Optimization”, J. of artificial Evolution and Applications. Vol. 1. 2008. pp. 1-14.
T. Havens, C. Spain, N. Salmon, J. Keller. “Roach Infestation Optimization”. IEEE Swarm Intelligence Symposium. St. Louis (MO). 2008. pp. 21-23.
A. Carlisle. Applying the particle swarm optimizer to non-stationary environments. Ph.D. Thesis. Auburn University. Auburn (USA). 2002. pp. 1-120.
J. Nanbo. Particle swarm optimization in engineering electromagnetic. Ph.D. Thesis. University of California. Los Ángeles (CA). 2008. pp. 1-135.
K. Byung. Parallel algorithms for biomedical optimization problems. Ph.D.Thesis. University of Florida. Gainesville (FL). 2005. pp. 1-167.
M. Clerc. Particle Swarm Optimization Ed. Prentice Hall. Chippenham (Great Britain). Chapter 4. 2006. pp. 69-79.
J. Kennedy, R. Eberhart. “Particle Swarm Optimization”. Proc. IEEE Int. Conf. Neural Networks. Piscataway (USA). 1995. pp. 1942-1948.
http://proquest.umi.com/pqdweb. Databases ProQuestMR. Consultado el 8 de mayo de 2009.
A. Lazinica. Particle Swarm Optimization, Ed. In- Tech. Vienna (Austria). 2009. pp. 1-486.
J Nealder, R. Mead. “A Simplex method for function minimization”. Computer Journal. Vol.7.1965. pp. 308-313.
F. Chia, C. Hsu. “Temperature control by chip implemented adaptive recurrent fuzzy controller designed by evolutionary algorithm.” IEEE Transactions on circuits and systems. Vol. 52. 2005. pp. 2376-2384.
S. Shu-Kai, E. Zhara. “A hybrid simplex search and particle swarm optimization for unconstrained optimization”. Euro. J. of Operational Research. Vol. 2. 2007. pp. 527-548.
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