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• W2337271819 abstract "Animal migration optimization (AMO) searches optimization solutions by migration process and updating process. In this paper, a novel migration process has been proposed to improve the exploration and exploitation ability of the animal migration optimization. Twenty-three typical benchmark test functions are applied to verify the effects of these improvements. The results show that the improved algorithm has faster convergence speed and higher convergence precision than the original animal migration optimization and other some intelligent optimization algorithms such as particle swarm optimization (PSO), cuckoo search (CS), firefly algorithm (FA), bat-inspired algorithm (BA) and artificial bee colony (ABC)." @default.
• W2337271819 created "2016-06-24" @default.
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• W2337271819 date "2016-01-01" @default.
• W2337271819 modified "2023-10-16" @default.
• W2337271819 title "A novel animal migration algorithm for global numerical optimization" @default.
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• W2337271819 doi "https://doi.org/10.2298/csis141229041l" @default.
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