A Novel Bat Algorithm with Multiple Strategies Coupling for Numerical Optimization

Author(s)

Wang, Yechuang ; Wang, Penghong; Zhang, Jiangjiang; Cui, Zhihua; Cai, Xingjuan; Zhang, Wensheng; Chen, Jinjun

Abstract

A bat algorithm (BA) is a heuristic algorithm that operates by imitating the echolocation behavior of bats to perform global optimization. The BA is widely used in various optimization problems because of its excellent performance. In the bat algorithm, the global search capability is determined by the parameter loudness and frequency. However, experiments show that each operator in the algorithm can only improve the performance of the algorithm at a certain time. In this paper, a novel bat algorithm with multiple strategies coupling (mixBA) is proposed to solve this problem. To prove the effectiveness of the algorithm, we compared it with CEC2013 benchmarks test suits. Furthermore, theWilcoxon and Friedman tests were conducted to distinguish the differences between it and other algorithms. The results prove that the proposed algorithm is significantly superior to others on the majority of benchmark functions.

Publication year

2019

Publication type

Journal article

Source

Mathematics, Vol. 7, no. 2 (Feb 2019), article no. 135

ISSN

2227-7390

Publisher

MDPI AG

Copyright

Copyright © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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