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ISSWOA: hybrid algorithm for function optimization and engineering problems

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Abstract

A hybrid algorithm based on the sparrow search algorithm (SSA) and whale optimization algorithm (WOA) is proposed to address numerical and engineering optimization problems. The hybrid algorithm has enhanced global search ability through the WOA's improved spiral update mechanism, so that it does not easily fall into the local optimum. Further, using the guard mechanism of SSA introduced by the Levy flight, it has a strong ability to escape from the local optimum. The performance of the improved sparrow search whale optimization algorithm (ISSWOA) was investigated using 23 benchmark functions (classified into standard unimodal, multimodal, and fixed-dimension multimodal benchmark functions) and compared with similar algorithms. The experimental results indicated that ISSWOA was significantly superior to other algorithms on most benchmark functions. To evaluate the performance of ISSWOA in complex engineering problems, seven engineering design problems and a large electrical engineering problem were solved using ISSWOA. Compared with other algorithms, the results showed that ISSWOA had high potential for practical engineering problems.

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Funding

This work was supported by the National Natural Science Foundation of China Program under Grant 62073198.

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  1. College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China

    Jianhui Zhang, Xuezhen Cheng, Meng Zhao & Jiming Li

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  1. Jianhui Zhang
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  2. Xuezhen Cheng
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  4. Jiming Li
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Contributions

JZ and XC proposed the innovation and designed the experiment in this study, JZ, MZ, and JL performed the simulation experiments and analyzed the experiment results and wrote the manuscript, JL corrected the manuscript.

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Correspondence to Jiming Li.

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Zhang, J., Cheng, X., Zhao, M. et al. ISSWOA: hybrid algorithm for function optimization and engineering problems. J Supercomput 79, 8789–8842 (2023). https://doi.org/10.1007/s11227-022-04996-1

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