Enhancing the performance of cuckoo search algorithm using orthogonal learning method

The cuckoo search algorithm is a simple and effective global optimization algorithm. It has been successfully applied to solve a wide range of real-world optimization problem. In this paper, we use a new search strategy based on orthogonal learning strategy to enhance the exploitation ability of the...

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Bibliographic Details
Published in:Neural computing & applications 2014-05, Vol.24 (6), p.1233-1247
Main Authors: Li, Xiangtao, Wang, Jianan, Yin, Minghao
Format: Article
Language:English
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
Original Article
Probability and Statistics in Computer Science
Theoretical computing
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Summary:The cuckoo search algorithm is a simple and effective global optimization algorithm. It has been successfully applied to solve a wide range of real-world optimization problem. In this paper, we use a new search strategy based on orthogonal learning strategy to enhance the exploitation ability of the basic cuckoo search algorithm. In order to verify the performance of our approach, 23 benchmark functions are employed. Experimental results indicate that the proposed algorithm performs better than or at least comparable to state-of-the-art approaches from literature when considering the quality of the solution obtained.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-013-1354-6