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An improved bat algorithm with velocity weight and curve decreasing

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Abstract

A bat algorithm (BA) is a heuristic algorithm that operates by imitating the echolocation behavior of bats to perform global optimization, which has fast convergence, a simple structure, and strong search ability. One of the issues in the standard bat algorithm is the premature convergence that can occur due to the low exploration ability of the algorithm under some conditions. To overcome this problem, the paper proposes a hybrid approach to improving its local search mechanism. The local search strategy of curve decreasing and speed weight is introduced to the standard bat algorithm to enhance its exploration and exploitation capabilities. The performance of the improved bat algorithm has better global optimization ability and higher convergence accuracy than the standard bat algorithm.

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Authors and Affiliations

  1. Guangdong Industry Polytechnic, Guangzhou, 510300, China

    Yun Ye & Xiaojuan Zhao

  2. College of Automation, Zhongkai University of Agriculture and Engineering, Guangzhou, 510070, Guangdong, China

    Lu Xiong

Authors
  1. Yun Ye
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  2. Xiaojuan Zhao
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  3. Lu Xiong
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Correspondence to Lu Xiong.

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Ye, Y., Zhao, X. & Xiong, L. An improved bat algorithm with velocity weight and curve decreasing. J Supercomput 78, 12461–12475 (2022). https://doi.org/10.1007/s11227-022-04368-9

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  • DOI: https://doi.org/10.1007/s11227-022-04368-9

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