The Cuckoo Search Algorithm Based on Dynamic Grouping to Adjust Flight Scale

Yi Ge Xue; Hui Wen Deng

doi:10.4028/www.scientific.net/AMM.543-547.1822

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 543-547The Cuckoo Search Algorithm Based on Dynamic...

The Cuckoo Search Algorithm Based on Dynamic Grouping to Adjust Flight Scale

Abstract:

The cuckoo search (CS) algorithm is a very efficient swarm optimization algorithm. Based on CS, a cuckoo search algorithm based on dynamic grouping to adjust flight scale (DGCS) is proposed: All cuckoos are divided into three groups according to the fitness of the individual and the average fitness of the population, then different flight scale is adopted dynamically for each group. Simulation experiments show that the DGCS can quickly converge to the global optimum solution, and has better optimization performance.

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Periodical:

Applied Mechanics and Materials (Volumes 543-547)

Pages:

1822-1826

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.543-547.1822

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Online since:

March 2014

Authors:

Yi Ge Xue, Hui Wen Deng*

Keywords:

Cuckoo Search, Levy Flight, Swarm Intelligence

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* - Corresponding Author

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