Abstract: Considering that the convergence of beetle antennae search algorithm (BAS) is of highly individual dependence, poor exploration ability and easily falling into local optimal solution, a beetle antennae search algorithm based on differential evolution strategy (BASD) is proposed. The algorithm not only uses the good point set method to initialize the beetle population to enhance the population diversity, but also introduces the concept of dynamic differential evolution to an elite evolutionary competition guidance strategy, which better balances the mining and exploration capabilities of the algorithm. The BASD algorithm is tested on 14 benchmark functions and compared with the optimization results of several advanced algorithms. The results show that the overall optimization performance of the BASD algorithm is better. Finally, the BASD algorithm is applied in image enhancement, and the result shows that the gray distribution of the image enhanced by the BASD algorithm is more uniform and the distribution range is larger.

Key words: beetle antennae search, differential evolution, theory of good point set, image enhancement