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Chaotic oppositional sine–cosine method for solving global optimization problems

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Abstract

This study proposed an improved sine–cosine algorithm (SCA) for global optimization tasks. The SCA is a meta-heuristic method ground on sine and cosine functions. It has found its application in many fields. However, SCA still has some shortcomings such as weak global search ability and low solution quality. In this study, the chaotic local search strategy and the opposition-based learning strategy are utilized to strengthen the exploration and exploitation capability of the basic SCA, and the improved algorithm is called chaotic oppositional SCA (COSCA). The COSCA was validated on a comprehensive set of 22 benchmark functions from classical 23 functions and CEC2014. Simulation experiments suggest that COSCA’s global optimization ability is significantly improved and superior to other algorithms. Moreover, COSCA is evaluated on three complex engineering problems with constraints. Experimental results show that COSCA can solve such problems more effectively than different algorithms.

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Acknowledgements

This research was supported by Guangdong Natural Science Foundation (2018A030313339), MOE (Ministry of Education in China) Youth Fund Project of Humanities and Social Sciences (17YJCZH261), and Scientific Research Team Project of Shenzhen Institute of Information Technology (SZIIT2019KJ022).

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  1. Mingjing Wang, Huiling Chen, and Chengye Li contributed equally to this work.

Authors and Affiliations

  1. College of Mathematics and Physics, Wenzhou University, Wenzhou, China

    Xi Liang

  2. College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, 325035, China

    Zhennao Cai & Huiling Chen

  3. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam

    Mingjing Wang

  4. School of Digital Media, Shenzhen Institute of Information Technology, Shenzhen, 518172, China

    Xuehua Zhao

  5. Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China

    Chengye Li

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  1. Xi Liang
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  2. Zhennao Cai
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  4. Xuehua Zhao
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Correspondence to Mingjing Wang, Huiling Chen or Chengye Li.

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Liang, X., Cai, Z., Wang, M. et al. Chaotic oppositional sine–cosine method for solving global optimization problems. Engineering with Computers 38, 1223–1239 (2022). https://doi.org/10.1007/s00366-020-01083-y

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