Cuckoo search algorithm with different distribution strategy
by Hengliang Tang; Fei Xue
International Journal of Bio-Inspired Computation (IJBIC), Vol. 13, No. 4, 2019

Abstract: Cuckoo search (CS) is a new meta-heuristic search algorithm based on the obligate nest parasitism of cuckoos and combining the characteristic flight of some birds and fruit flies. In order to study the influence of distribution strategy on cuckoo search algorithm, in the paper, introduces Cauchy distribution, Gaussian distribution, Uniform distribution and Levy distribution, analysis the performance of cuckoo search algorithm by the method of pair combination. In order to verify the effectiveness of the algorithm, 28 typical test functions proposed by CEC2013 were taken as examples for testing, and the experimental results showed the effectiveness of the algorithm. Simulation results show that the hybrid distribution of Levy distribution and Cauchy distribution can make the cuckoo search algorithm perform better.

Online publication date: Wed, 12-Jun-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Bio-Inspired Computation (IJBIC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com