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A hybrid algorithm based on cuckoo search and differential evolution for numerical optimization

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DOI: 10.23977/cpcs.2020.41001 | Downloads: 1 | Views: 71

Author(s)

Jun Xi 1, Liming Zheng 1

Affiliation(s)

1 School of Information Science and Technology, Jinan University, Guangzhou, 510632, China

Corresponding Author

Liming Zheng

ABSTRACT

Cuckoo search (CS) is a new intelligent bionic algorithm, but it is easy to fall into the local optimum. In this paper, a hybrid algorithm based on cuckoo search and differential evolution (CSDE) is proposed. In the global optimization, a control factor is introduced to judge the optimization state of CS, further determine whether it is necessary to combine the differential strategy to improve the population diversity. Besides, different evolutionary strategies are used to enhance the local search. Numerical experiments, carried on 28 benchmark functions from CEC 2013, demonstrate that CSDE successfully achieves better optimization performance than other competitive optimization algorithms.

KEYWORDS

Cuckoo search; Differential evolution; Numerical optimization

CITE THIS PAPER

Jun Xi, Liming Zheng. A hybrid algorithm based on cuckoo search and differential evolution for numerical optimization, Performance and Communication Systems (2020) Vol. 4: 1-8. DOI: http://dx.doi.org/10.23977/cpcs.2020.41001.

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