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Sine–cosine crow search algorithm: theory and applications

  • Soft Computing Techniques: Applications and Challenges
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Abstract

In this paper, we propose a new hybrid algorithm called sine–cosine crow search algorithm that inherits advantages of two recently developed algorithms, including crow search algorithm (CSA) and sine–cosine algorithm (SCA). The exploration and exploitation capabilities of the proposed algorithm have significantly improved. Performance of the so-called SCCSA was evaluated in unimodal, multimodal, fixed-dimensional multimodal and composite benchmark functions using robust measures. Based on in-depth analyses and statistical information, we showed that the suggested methodology could provide promising solutions comparing to other state-of-the-art algorithms.

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Authors and Affiliations

  1. Department of Mechanical, Industrial and Aerospace Engineering (MIAE), Concordia University, Montreal, Canada

    Soheyl Khalilpourazari

  2. Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran

    Seyed Hamid Reza Pasandideh

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  1. Soheyl Khalilpourazari
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  2. Seyed Hamid Reza Pasandideh
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Correspondence to Seyed Hamid Reza Pasandideh.

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Khalilpourazari, S., Pasandideh, S.H.R. Sine–cosine crow search algorithm: theory and applications. Neural Comput & Applic 32, 7725–7742 (2020). https://doi.org/10.1007/s00521-019-04530-0

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  • DOI: https://doi.org/10.1007/s00521-019-04530-0

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