Orthogonal Genetic Algorithm and its Application in Function Optimization

Abstract:

Article Preview

Traditional genetic algorithm trapped into the local minimum easily. Therefore, based on a simple genetic algorithm and combine the base ideology of orthogonal test then applied it to the population initialization, crossover operator, as well as the introduction of adaptive orthogonal local search to prevent local convergence to form a new orthogonal evolutionary algorithm. Through the series of numerical experiments, proved the efficiency of the new algorithm.

Info:

Periodical:

Edited by:

Dongye Sun, Wen-Pei Sung and Ran Chen

Pages:

4528-4531

DOI:

10.4028/www.scientific.net/AMM.121-126.4528

Citation:

H. M. Liu et al., "Orthogonal Genetic Algorithm and its Application in Function Optimization", Applied Mechanics and Materials, Vols. 121-126, pp. 4528-4531, 2012

Online since:

October 2011

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Price:

$35.00

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