Open AccessTwo New Beetle Antennae Search (BAS) Algorithms and Their Comparative Investigation
Author(s) -
Zongyuan Lin,
Sile Ma,
Xiang Ma,
Xiangyuan Jiang,
Shuai Li
Publication year - 2018
Publication title -
international journal of robotics and control
Language(s) - English
Resource type - Journals
eISSN - 2577-7769
pISSN - 2577-7742
DOI - 10.5430/ijrc.v2n1p9
Subject(s) - benchmark (surveying) , algorithm , search algorithm , reliability (semiconductor) , stability (learning theory) , local search (optimization) , computer science , best first search , heuristic , mathematical optimization , beam search , mathematics , artificial intelligence , machine learning , power (physics) , physics , geodesy , quantum mechanics , geography
The Beetle Antennae Search (BAS) algorithm is a meta-heuristic search algorithm, which has efficient search capabilities. This paper presents two different variant algorithms based on the BAS algorithm, which are the BAS with fitness value (BASF) algorithm and BAS with local fast search (BASL) algorithm. The test results of 23 benchmark functions will be used to verify the reliability and accuracy of these algorithm. These benchmark functions include unimodal and multimodal high-dimensional functions, as well as fixed-dimensional multimodal functions. The test results show that the improved algorithm can search for the optimal solution globally and accurately with its own search strategy without environment parameters. Stability and accuracy are significantly improved while the calculation time does not change much.