Bat algorithm with principal component analysis

02 engineering and technology 0201 civil engineering
DOI: 10.1007/s13042-018-0888-4 Publication Date: 2018-11-30T15:21:15Z
ABSTRACT
The bat algorithm (BA) is a novel evolutionary optimization algorithm, most studies of which have been performed with low-dimensional problems. To test and improve the global search ability of BA with large-scale problems, two new variants using principal component analysis (PCA_BA and PCA_LBA) are designed in this paper. A correlation threshold and generation threshold are determined using the golden section method to enhance the effectiveness of this new strategy. To test performance, CEC’2008 large-scale benchmark functions are utilized and compared with other algorithms; simulation results indicate the validity of this modification.
SUPPLEMENTAL MATERIAL
Coming soon ....
REFERENCES (50)
CITATIONS (72)
EXTERNAL LINKS
PlumX Metrics
RECOMMENDATIONS
FAIR ASSESSMENT
Coming soon ....
JUPYTER LAB
Coming soon ....