Neural Computing and Applications

, Volume 24, Issue 1, pp 169–174

Cuckoo search: recent advances and applications

Invited Review

DOI: 10.1007/s00521-013-1367-1

Cite this article as:
Yang, XS. & Deb, S. Neural Comput & Applic (2014) 24: 169. doi:10.1007/s00521-013-1367-1
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Abstract

Cuckoo search (CS) is a relatively new algorithm, developed by Yang and Deb in 2009, and the same has been found to be efficient in solving global optimization problems. In this paper, we review the fundamental ideas of cuckoo search and the latest developments as well as its applications. We analyze the algorithm and gain insight into its search mechanisms and find out why it is efficient. We also discuss the essence of algorithms and its link to self-organizing systems, and finally, we propose some important topics for further research.

Keywords

Cuckoo search Convergence Swarm intelligence optimization Metaheuristic Nature-inspired algorithm 

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  1. 1.School of Science and TechnologyMiddlesex UniversityLondonUK
  2. 2.Cambridge Institute of TechnologyRanchiIndia

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