Abstract
The article firstly introduces two respective theories on research and evolvement about Wolf Pack Intelligent Optimization Algorithm, and compares with the differences and similarities between the two theories. It also illustrates the differences in performance on optimization solution through the experimental result. Then, it concludes the improvement research on wolf pack algorithm, focused on the improvement on parameter setting and hybrid algorithm. Thirdly, the article elaborates the typical applications about wolf pack algorithm on function optimization, combination optimization and engineering optimization. At last, the article summarizes the deficiency in the research and proposes the research goal of next step.
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Yixiao, S., Renjun, Z., Husheng, W., Zhexin, H., Yanbin, M. (2017). Review and Research Development of Optimization Algorithms Based on Wolf Intelligence. In: Xhafa, F., Barolli, L., Amato, F. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2016. Lecture Notes on Data Engineering and Communications Technologies, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-49109-7_53
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DOI: https://doi.org/10.1007/978-3-319-49109-7_53
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