Bat Algorithm with Adaptive Speed
As a famous heuristic algorithm, bat algorithm (BA) simulates the behavior of bat echolocation, which has simple model, fast convergence and distributed characteristics. But it also has some defects like slow convergence and low optimizing accuracy. Facing the shortages above, an optimization bat algorithm based on adaptive speed strategy is proposed. This improved algorithm can simulate the bat in the process of search based on adaptive value size and adaptive speed adjustment. His approach can improve the optimization efficiency and accuracy. Experimental results on CEC2013 test benchmarks show that our proposal has better global searchability and a faster convergence speed, and can effectively overcome the problem convergence.
KeywordsHeuristic optimization algorithm Bat algorithm Convergence Adaptive speed
This work was supported by Beijing Key Laboratory (No: BZ0211) and Beijing Intelligent Logistics System Collaborative Innovation Center.
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