Bat algorithm is better than intermittent search strategy

Yang, Xin-She, Deb, Suash and Fong, Simon (2014) Bat algorithm is better than intermittent search strategy. Journal of Multiple-Valued Logic and Soft Computing, 22 (3). pp. 223-237. ISSN 1542-3980

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Abstract

The efficiency of any metaheuristic algorithm largely depends on the way of balancing local intensive exploitation and global diverse exploration. Studies show that bat algorithm can provide a good balance between these two key components with superior efficiency. In this paper, we first review some commonly used metaheuristic algorithms, and then compare the performance of bat algorithm with the so-called intermittent search strategy. From simulations, we found that bat algorithm is better than the optimal intermittent search strategy. We also analyse the comparison results and their implications for higher dimensional optimization problems. In addition, we also apply bat algorithm in solving business optimization and engineering design problems.

Item Type: Article
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 19343
Useful Links:
Depositing User: Xin-She Yang
Date Deposited: 19 Apr 2016 09:51
Last Modified: 13 Oct 2016 14:39
URI: https://eprints.mdx.ac.uk/id/eprint/19343

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