Updated 28 Apr 2021
In order to solve the problem that the butterfly optimization algorithm (BOA) is prone to low
accuracy and slow convergence, the trend of study is to hybridize two or more algorithms to obtain a
superior solution in the field of optimization problems. A novel hybrid algorithm is proposed, namely
HPSOBOA, and three methods are introduced to improve the basic BOA. Therefore, the initialization
of BOA using a cubic one-dimensional map is introduced, and a nonlinear parameter control strategy
is also performed. In addition, the particle swarm optimization (PSO) algorithm is hybridized with
BOA in order to improve the basic BOA for global optimization. There are two experiments (including
26 well-known benchmark functions) that were conducted to verify the effectiveness of the proposed
algorithm. The comparison results of experiments show that the hybrid HPSOBOA converges quickly
and has better stability in numerical optimization problems with a high dimension compared with
the PSO, BOA, and other kinds of well-known swarm optimization algorithms.
M. J. ZHANG (2021). HPSOBOA v1.0 (https://www.mathworks.com/matlabcentral/fileexchange/91155-hpsoboa-v1-0), MATLAB Central File Exchange. Retrieved .
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