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Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems

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An Erratum to this article was published on 12 December 2012

Abstract

In this study, a new metaheuristic optimization algorithm, called cuckoo search (CS), is introduced for solving structural optimization tasks. The new CS algorithm in combination with Lévy flights is first verified using a benchmark nonlinear constrained optimization problem. For the validation against structural engineering optimization problems, CS is subsequently applied to 13 design problems reported in the specialized literature. The performance of the CS algorithm is further compared with various algorithms representative of the state of the art in the area. The optimal solutions obtained by CS are mostly far better than the best solutions obtained by the existing methods. The unique search features used in CS and the implications for future research are finally discussed in detail.

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Acknowledgments

The authors gratefully acknowledge the work and help of Engineer Parvin Arjmandi (Tafresh University).

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Authors and Affiliations

  1. Department of Civil Engineering, Tafresh University, Tafresh, Iran

    Amir Hossein Gandomi

  2. Mathematics and Scientific Computing, National Physical Lab, Teddington, TW11 0LW, UK

    Xin-She Yang

  3. School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran, Iran

    Amir Hossein Alavi

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  1. Amir Hossein Gandomi
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  2. Xin-She Yang
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Correspondence to Amir Hossein Gandomi.

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Gandomi, A.H., Yang, XS. & Alavi, A.H. Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Engineering with Computers 29, 17–35 (2013). https://doi.org/10.1007/s00366-011-0241-y

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