An Improved Hybrid Genetic Algorithm and Performance Study

Article Preview

Abstract:

Put forward a kind of the hybrid improved genetic algorithm of particle swarm optimization method (PSO) combine with and BFGS algorithm of, this method using PSO good global optimization ability and the overall convergence of BFGS algorithm to overcome the blemish of in the conventional algorithm slow convergence speed and precocious and local convergence and so on. Through the three typical high dimensional function test results show that this method not only improved the algorithm of the global search ability, to speed up the convergence speed, but also improve the quality of the solution and its reliability of optimization results.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 482-484)

Pages:

95-98

Citation:

Online since:

February 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Y.W. Leung and Y.P. Wang.. IEEE Transactions on Evolutionary Computation.2001,5(1),p.41

Google Scholar

[2] J.LIN. Journal of Nanjing University of Posts and Telecommunications.2004,24(4),p.59. In Chinese.

Google Scholar

[3] K.Z. LU, R..C.WANG, and J.S. ZHANG. Application Research of Computers.2007,24(5),p.17.In Chinese.

Google Scholar

[4] Y.Shi, R.C. Eberhart.A modified particle swarm optimizer[C].Proc. IEEE Int. Conf. Evol. Comput., Anchorage, Alaska, May (1998), 69-73.

Google Scholar