Paper Title:
A Novel Global Optimization Method – Genetic Pattern Search
  Abstract

A novel global optimization method is proposed to find global minimal points more effectively and quickly. The new algorithm is based on both genetic algorithms (GA) and pattern search (PS) algorithms, thus, we have named it genetic pattern search. The procedure involves two-phases: First, GA executes a coarse search, PS then executes a fine search. Experiments on four different test functions (consisting of Hump, Powell, Rosenbrock, and Woods) demonstrate that this proposed new algorithm is superior to improved GA and improved PS with respect to success rate and computation time. Therefore, genetic pattern search is an effective and viable global optimization method.

  Info
Periodical
Edited by
Ran Chen
Pages
3240-3244
DOI
10.4028/www.scientific.net/AMM.44-47.3240
Citation
Y. D. Zhang, L. N. Wu, Y. K. Huo, S. H. Wang, "A Novel Global Optimization Method – Genetic Pattern Search", Applied Mechanics and Materials, Vols. 44-47, pp. 3240-3244, 2011
Online since
December 2010
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