Abstract
After analyzing the deficiencies of bat algorithm (BA), we proposed an improved bat algorithm called an adaptive bat algorithm(ABA). In the ABA, each bat can dynamic and adaptively adjust its flight speed and its flight direction while it is searching for food, and makes use of the hunting approach of combining random search with shrinking search. The experimental results show that the ABA not only has marked advantage of global convergence property but also can effectively avoid the premature convergence problem. © 2013 Springer-Verlag.
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Wang, X., Wang, W., & Wang, Y. (2013). An adaptive bat algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7996 LNAI, pp. 216–223). https://doi.org/10.1007/978-3-642-39482-9_25
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