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| A variational butterfly algorithm incorporating the sine-cosine strategy |
| LI Pengtao 1**,WANG Haibo 2*,,LI Zhifeng 1***,WANG Ronglin 2**,WEN Hao2** , LIU Chunjie 2**
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1 School of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin City, 132022,China;
2 School of Mechanical and Electrical Engineering, Jilin Institute of Chemical Technology, Jilin City 132022,China
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Abstract To address the issues of low precision, susceptibility to local optima, and slow convergence speed in the basic Butterfly Optimization Algorithm (BOA), this paper proposes a variant butterfly algorithm incorporating a sine-cosine strategy. First, the population is initialized using a Bernoulli chaotic map, resulting in a more uniform distribution. Next, adaptive weight coefficients are introduced to improve the speed and precision of global and local position updates. Then, in the local position search phase, the Sine-Cosine Algorithm (SCA) is integrated, with a dynamic switching probability to control the use of SCA, thereby enhancing the algorithm's local search capability. Finally, a Gaussian mutation strategy is employed to mutate the optimal solution, enhancing the algorithm's ability to escape local optima. Simulation experiments on eight benchmark test functions demonstrate that the improved algorithm shows significant competitiveness and better performance compared to other algorithms.
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Published: 25 May 2024
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