Improved Bat Algorithm Based on Fast Diving Strategy

Improved Bat Algorithm Based on Fast Diving Strategy

Bat algorithm has good global search ability, but it has some problems, such as slow convergence speed in local search stage, low convergence accuracy, easy to fall into local optimization and can not escape. In view of the above defects, inspired by Harris Hawks’s strategy of catching rabbits, this paper introduces the surrounding mechanism of prey, which can quickly approach the food and judge its quality, so as to achieve the purpose of rapid convergence and improve the convergence accuracy. The experiment shows that the improved algorithm of the fast diving strategy is tested by using the test function, and compared with the basic bat algorithm, backtracking bat algorithm and HABC. The improved bat algorithm of the fast diving strategy has better optimization accuracy, faster convergence speed, simple algorithm and higher success rate.