An Improved Beetle Antennae Search Algorithm Based on Inertia Weight and Attenuation Factor

Abstract

The beetle antennae search algorithm is an effective bio-inspired algorithm. However, the algorithm is easy to fall into local optimal solution when dealing with high-dimensional and multimodal problems. An improved beetle antennae search algorithm based on inertia weight and attenuation factor was proposed in order to solve the problems. The inertia weights of normal distribution, versoria distribution, and random distribution are introduced into the weight to improve the search strategy, which was introduced to control the proportion of global search and local search so that the algorithm will escape the local optimum. Meanwhile, the randomness is introduced in the process of beetle’s step-size update, which can better help beetle to escape from the local optimum. Experiments on some benchmarks show that the algorithm has obvious performance improvement in dealing with high-dimensional and multimodal problems.