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• W1539941192 abstract "The search for efficient and reliable bio-inspired optimization methods continues to be an active topic of research due to the wide application of the developed methods. In this study, we developed a reliable and efficient optimization method via the hybridization of two bio-inspired swarm intelligence optimization algorithms, namely, the Monkey Algorithm (MA) and the Krill Herd Algorithm (KHA). The hybridization made use of the efficient steps in each of the two original algorithms and provided a better balance between the exploration/diversification steps and the exploitation/intensification steps. The new hybrid algorithm, MAKHA, was rigorously tested with 27 benchmark problems and its results were compared with the results of the two original algorithms. MAKHA proved to be considerably more reliable and more efficient in tested problems." @default.
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• W1539941192 date "2015-06-19" @default.
• W1539941192 modified "2023-10-16" @default.
• W1539941192 title "MAKHA—A New Hybrid Swarm Intelligence Global Optimization Algorithm" @default.
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• W1539941192 doi "https://doi.org/10.3390/a8020336" @default.
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