Bat algorithm(BA) is a new swarm intelligence optimization algorithm. However, bat algorithm has the obvious phenomenon of the premature convergence problem and is easily trapped into local optimum. In order to overcome the shortcoming of the BA algorithm, we proposed an improved bat algorithm called bat algorithm with recollection(RBA). Experiment were conducted on some benchmark functions. The experimental results show that the RBA can effectively avoid the premature convergence problem and has a good performance of global convergence property.
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