Differential evolution algorithm combined with chaotic pattern search

Title:

Differential evolution algorithm combined with chaotic pattern search

Creator:

He, Yaoyao, Zhou, Jian Zhong, Lu, Ning, Qin, Hui, and Lu, Youlin

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:f8d412a8-0db9-4c20-a9b9-8cd2bea38d1b
uuid:f8d412a8-0db9-4c20-a9b9-8cd2bea38d1b

Subject:

hybrid algorithm, differential evolution (DE), chaotic pattern search, and global optimization

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

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.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Coverage:

[684]-696

Source:

Kybernetika | 2010 Volume:46 | Number:4

Harvested from:

CDK

Metadata only:

false