Abstract
The Memory-based Bees Algorithm (MBA) is a new optimisation algorithm based on the Bees Algorithm (BA). MBA includes private and social information of honey bees to copy the decision-making capability of the bees. Lévy flights are random processes that are based on a stable distribution called the Lévy distribution. The enhanced so-called Levy MBA (LMBA) is used to reduce the tunable parameters of the basic BA and MBA algorithms. It is tested for Otsu’s multilevel image thresholding method with the peak signal-to-noise ratio (PSNR) as the thresholding quality measurement. The objective is to find optimal threshold values, particularly with the highest quality. The results demonstrated several benchmark problems with the efficiency and robustness of the new algorithm.
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This research is funded under the Ministry of Higher Education of Malaysia with the code FRGS/1/2016/ICT02/UKM/02/10.
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Shatnawi, N., Sahran, S., Nasrudin, M.F. (2023). Memory-Based Bees Algorithm with Lévy Flights for Multilevel Image Thresholding. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_11
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