The article is available online here https://doi.org/10.1007/s10462-024-10723-4 or as a PDF here https://link.springer.com/content/pdf/10.1007/s10462-024-10723-4.pdf .
To apply this code, please refer to the following paper:Jun Wang, Wen-chuan Wang, Xiao-xue Hu, Lin Qiu, Hong-fei Zang. Black-winged Kite Algorithm: A nature-inspired meta-heuristic for Solving benchmark functions and Engineering problems. Artificial Intelligence Review, 2024, 57:98 https://doi.org/10.1007/s10462-024-10723-4
This paper innovatively proposes the Black Kite Algorithm (BKA), a meta-heuristic optimization algorithm inspired by the migratory and predatory behavior of the black kite. The BKA integrates the Cauchy mutation strategy and the Leader strategy to enhance the global search capability and the convergence speed of the algorithm. This novel combination achieves a good balance between exploring global solutions and utilizing local information. Against the standard test function sets of CEC-2022 and CEC-2017, as well as other complex functions, BKA attained the best performance in 66.7%, 72.4%, and 77.8% of the cases, respectively. The effectiveness of the algorithm is validated through detailed convergence analysis and statistical comparisons. Moreover, its application in solving five practical engineering design problems demonstrates its practical potential in addressing constrained challenges in the real world and indicates that it has significant competitive strength in comparison with existing optimization techniques. In summary, the BKA has proven its practical value and advantages in solving a variety of complex optimization problems due to its excellent performance.
引用格式
Wen-chuan Wang (2024). Black-winged Kite Algorithm(BKA) (https://www.mathworks.com/matlabcentral/fileexchange/161401-black-winged-kite-algorithm-bka), MATLAB Central File Exchange. 检索时间: .
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1.1.2 | A nature-inspired meta-heuristic for Solving benchmark functions and Engineering problems |
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1.1.0 | The article is available online here https://doi.org/10.1007/s10462-024-10723-4 or as a PDF here https://link.springer.com/content/pdf/10.1007/s10462-024-10723-4.pdf . |
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