Loading...
Please wait, while we are loading the content...
A Chaotic Hybrid Butterfly Optimization Algorithm with Particle Swarm Optimization for High-Dimensional Optimization Problems
| Content Provider | MDPI |
|---|---|
| Author | Zhang, Mengjian Long, Daoyin Qin, Tao Yang, Jing |
| Copyright Year | 2020 |
| Description | 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. |
| Starting Page | 1800 |
| e-ISSN | 20738994 |
| DOI | 10.3390/sym12111800 |
| Journal | Symmetry |
| Issue Number | 11 |
| Volume Number | 12 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2020-10-30 |
| Access Restriction | Open |
| Subject Keyword | Symmetry Hardware and Architecturee Butterfly Optimization Algorithm (boa) Particle Swarm Optimization (pso) Cubic Map Nonlinear High Dimension |
| Content Type | Text |
| Resource Type | Article |
