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Gaussian Bare-Bones Differential Evolution | IEEE Journals & Magazine | IEEE Xplore

Gaussian Bare-Bones Differential Evolution


Abstract:

Differential evolution (DE) is a well-known algorithm for global optimization over continuous search spaces. However, choosing the optimal control parameters is a challen...Show More

Abstract:

Differential evolution (DE) is a well-known algorithm for global optimization over continuous search spaces. However, choosing the optimal control parameters is a challenging task because they are problem oriented. In order to minimize the effects of the control parameters, a Gaussian bare-bones DE (GBDE) and its modified version (MGBDE) are proposed which are almost parameter free. To verify the performance of our approaches, 30 benchmark functions and two real-world problems are utilized. Conducted experiments indicate that the MGBDE performs significantly better than, or at least comparable to, several state-of-the-art DE variants and some existing bare-bones algorithms.
Published in: IEEE Transactions on Cybernetics ( Volume: 43, Issue: 2, April 2013)
Page(s): 634 - 647
Date of Publication: 07 March 2013

ISSN Information:

PubMed ID: 23014758

References

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