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Differential evolution algorithm combined with chaotic pattern search

Yaoyao He; Jianzhong Zhou; Ning Lu; Hui Qin; Youlin Lu

Kybernetika (2010)

  • Volume: 46, Issue: 4, page 684-696
  • ISSN: 0023-5954

Abstract

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Differential evolution algorithm combined with chaotic pattern search(DE-CPS) for global optimization is introduced to improve the performance of simple DE algorithm. Pattern search algorithm using chaotic variables instead of random variables is used to accelerate the convergence of solving the objective value. Experiments on 6 benchmark problems, including morbid Rosenbrock function, show that the novel hybrid algorithm is effective for nonlinear optimization problems in high dimensional space. The comparisons with the standard particle swarm optimization (PSO), differential evolution (DE) and other hybrid algorithms verify DE-CPS algorithm has great superiority.

How to cite

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He, Yaoyao, et al. "Differential evolution algorithm combined with chaotic pattern search." Kybernetika 46.4 (2010): 684-696. <http://eudml.org/doc/196547>.

@article{He2010,
abstract = {Differential evolution algorithm combined with chaotic pattern search(DE-CPS) for global optimization is introduced to improve the performance of simple DE algorithm. Pattern search algorithm using chaotic variables instead of random variables is used to accelerate the convergence of solving the objective value. Experiments on 6 benchmark problems, including morbid Rosenbrock function, show that the novel hybrid algorithm is effective for nonlinear optimization problems in high dimensional space. The comparisons with the standard particle swarm optimization (PSO), differential evolution (DE) and other hybrid algorithms verify DE-CPS algorithm has great superiority.},
author = {He, Yaoyao, Zhou, Jianzhong, Lu, Ning, Qin, Hui, Lu, Youlin},
journal = {Kybernetika},
keywords = {hybrid algorithm; differential evolution(DE); chaotic pattern search; global optimization; hybrid algorithm; differential evolution; chaotic pattern search; global optimization; convergence acceleration; numerical examples; comparison of methods; nonlinear optimization; particle swarm optimization},
language = {eng},
number = {4},
pages = {684-696},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Differential evolution algorithm combined with chaotic pattern search},
url = {http://eudml.org/doc/196547},
volume = {46},
year = {2010},
}

TY - JOUR
AU - He, Yaoyao
AU - Zhou, Jianzhong
AU - Lu, Ning
AU - Qin, Hui
AU - Lu, Youlin
TI - Differential evolution algorithm combined with chaotic pattern search
JO - Kybernetika
PY - 2010
PB - Institute of Information Theory and Automation AS CR
VL - 46
IS - 4
SP - 684
EP - 696
AB - Differential evolution algorithm combined with chaotic pattern search(DE-CPS) for global optimization is introduced to improve the performance of simple DE algorithm. Pattern search algorithm using chaotic variables instead of random variables is used to accelerate the convergence of solving the objective value. Experiments on 6 benchmark problems, including morbid Rosenbrock function, show that the novel hybrid algorithm is effective for nonlinear optimization problems in high dimensional space. The comparisons with the standard particle swarm optimization (PSO), differential evolution (DE) and other hybrid algorithms verify DE-CPS algorithm has great superiority.
LA - eng
KW - hybrid algorithm; differential evolution(DE); chaotic pattern search; global optimization; hybrid algorithm; differential evolution; chaotic pattern search; global optimization; convergence acceleration; numerical examples; comparison of methods; nonlinear optimization; particle swarm optimization
UR - http://eudml.org/doc/196547
ER -

References

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