Cuckoo search: recent advances and applications

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 analyz...

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Bibliographic Details
Published in:Neural computing & applications Vol. 24; no. 1; pp. 169 - 174
Main Authors: Yang, Xin-She, Deb, Suash
Format: Journal Article
Language:English
Published: London Springer London 01.01.2014
Springer
Subjects:
Algorithmics. Computability. Computer arithmetics
Applied sciences
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Computer science; control theory; systems
Data Mining and Knowledge Discovery
Exact sciences and technology
Image Processing and Computer Vision
Invited Review
Probability and Statistics in Computer Science
Theoretical computing
Cuckoo search
Metaheuristic
Swarm intelligence optimization
Nature-inspired algorithm
Convergence
Artificial life
Parasite
Global optimum
Optimization
Self organization
Biomimetics
Heuristic method
Swarm intelligence
Artificial intelligence
Metamodel
Mathematical programming
ISSN:0941-0643, 1433-3058
Online Access:Get full text
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Summary: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.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-013-1367-1