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Springer, Berlin, Heidelberg

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10.1007/s10902-015-9659-z

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Firefly Algorithm and Pattern Search Hybridized for Global Optimization

Authors: Mahdiyeh Eslami, Hussain Shareef, Mohammad Khajehzadeh,

Publish Date: 2013/7/28
Volume: , Issue:, Pages: 172-178
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Abstract

Firefly optimization algorithm is one of the latest swarm intelligence based optimization algorithm. A new hybrid optimization algorithm, which combines pattern search with firefly algorithm, namely FAPS, is proposed for numerical global optimization. There are two alternative phases of the proposed algorithm: the global exploration phase realized by firefly algorithm and the exploitation phase completed by pattern search. The performance of the proposed FAPS algorithm was tested on a comprehensive set of benchmark functions. The numerical experiments demonstrate that the new algorithm has high viability, accuracy and stability and the performance of firefly algorithm is much improved by introducing a pattern search method.


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