Considering the fact that the original Bird Swarm Algorithm(BSA) in optimizing high-dimensional multi-extreme value easily gets locally optimal solution and premature convergence, an improved algorithm, Levy-Bird Swarm Algorithm(LBSA) is proposed, which is based on Levy flight, a simulation of the birds flying. LBSA replaces the random location changes in the original algorithm by using Levy flight to update the flight locations, which substantially increases the vitality of the location changes, and makes the algorithm more effective. The results of simulation show that the LBSA outperforms the original BSA in optimizing high-dimensional multi-extreme value.
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