BAS: Beetle Antennae Search Algorithm for Optimization Problems

By Xiangyuan Jiang, Shuai Li. arXiv.org, 2017

448 citations recorded by the source corpus.

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.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/a893b5785a54c1a1dc417baa1fb05dc6a5093f2d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Guichen Li
2. Deyu Qian
3. Yuantian Sun
4. Yuhang Wang
5. Junfei Zhang

In Computational Theory and Mathematics

1. Guichen Li
2. Deyu Qian
3. Yuantian Sun
4. Junfei Zhang

Citations in the corpus

• Optimized neural network using beetle antennae search for predicting the unconfined compressive strength of jet grouting coalcretes (2019, methodology): “BAS is a meta‐heuristic algorithm that was recently proposed with a powerful performance on optimization problems.(43) It is based on the behavior of beetles using two antennae to randomly explore nearby area and tune to a higher odor concentration.”
• Prediction of the Strength of Rubberized Concrete by an Evolved Random Forest Model (2019, methodology): “In this paper, a high-efficiency global optimization algorithm called the beetle antennae search (BAS) algorithm was applied to obtain the best parameters of RF [30].”