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A Levy Flight Sine Cosine Algorithm for Global Optimization Problems

A Levy Flight Sine Cosine Algorithm for Global Optimization Problems

Yu Li, Yiran Zhao, Jingsen Liu
Copyright: © 2021 |Volume: 12 |Issue: 1 |Pages: 18
ISSN: 1947-3532|EISSN: 1947-3540|EISBN13: 9781799861720|DOI: 10.4018/IJDST.2021010104
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MLA

Li, Yu, et al. "A Levy Flight Sine Cosine Algorithm for Global Optimization Problems." IJDST vol.12, no.1 2021: pp.49-66. http://doi.org/10.4018/IJDST.2021010104

APA

Li, Y., Zhao, Y., & Liu, J. (2021). A Levy Flight Sine Cosine Algorithm for Global Optimization Problems. International Journal of Distributed Systems and Technologies (IJDST), 12(1), 49-66. http://doi.org/10.4018/IJDST.2021010104

Chicago

Li, Yu, Yiran Zhao, and Jingsen Liu. "A Levy Flight Sine Cosine Algorithm for Global Optimization Problems," International Journal of Distributed Systems and Technologies (IJDST) 12, no.1: 49-66. http://doi.org/10.4018/IJDST.2021010104

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Abstract

The sine cosine algorithm (SCA) is a recently proposed global swarm intelligence algorithm based on mathematical functions. This paper proposes a Levy flight sine cosine algorithm (LSCA) to solve optimization problems. In the update equation, the levy flight is introduced to improve optimization ability of SCA. By generating a random walk to update the position, this strategy can effectively search for particles to maintain better population diversity. LSCA has been tested 15 benchmark functions and real-world engineering design optimization problems. The result of simulation experiments with LSCA, SCA, PSO, FPA, and other improvement SCA show that the LSCA has stronger robustness and better convergence accuracy. The engineering problems are also shown that the effectiveness of the levy flight sine cosine algorithm to ensure the efficient results in real-world optimization problem.

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