BAS: Beetle Antennae Search Algorithm for Optimization Problems

TL;DR

The paper introduces the Beetle Antennae Search (BAS) algorithm, inspired by beetle behavior, which effectively solves optimization problems and is validated on benchmark functions.

Contribution

It proposes a novel meta-heuristic algorithm inspired by beetle foraging behavior, demonstrating its effectiveness on standard test functions.

Findings

BAS performs well on benchmark functions

Numerical results validate the algorithm's efficacy

The method mimics natural beetle searching behavior

Abstract

Meta-heuristic algorithms have become very popular because of powerful performance on the optimization problem. A new algorithm called beetle antennae search algorithm (BAS) is proposed in the paper inspired by the searching behavior of longhorn beetles. The BAS algorithm imitates the function of antennae and the random walking mechanism of beetles in nature, and then two main steps of detecting and searching are implemented. Finally, the algorithm is benchmarked on 2 well-known test functions, in which the numerical results validate the efficacy of the proposed BAS algorithm.