An improved bat algorithm with Doppler effect for stochastic optimization

Bat Algorithm is a powerful nature-inspired method for solving many multi-objective optimization problems. This paper presents a novel algorithm which is called Doppler Effect Bat Algorithm (DEBA).This algorithm intends to combine Doppler effect with the bat algorithm. Based on bats' Doppler effect theory and the framework of the original bat algorithm, the new frequency equation in this algorithm is proposed, and the velocities and locations equation are also updated. The improved algorithm is also compared with PSO and the basic bat algorithm in the paper. In order to analyze the improvement on the accuracy of finding the near best solution and the reduction in the computational cost, five well-known and commonly used test functions are used in the experiments. Simulations show that the proposed algorithm seems much superior to PSO and the original bat algorithm.