### Research and Application of Beetle Antennae Genetic Hybrid Algorithm

FENG Xiaodong, HUANG Shirong, DAI Guan’ou, YANG Weijia, LUO Yaozhi

1. 1.College of Civil Engineering, Shaoxing University, Shaoxing, Zhejiang 312000, China
2.College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310000, China
• Online:2021-08-01 Published:2021-07-26

### 天牛须遗传杂交算法的研究与应用

1. 1.绍兴文理学院 土木工程学院，浙江 绍兴 312000
2.浙江大学 建筑与土木工程学院，杭州 310000

Abstract:

In order to improve the global search ability of the Adaptive Genetic Algorithm（AGA） under high-selection-pressures, a hybrid algorithm entitled Beetle Antennae-Genetic Algorithm（BAGA） is proposed based on Beetle Antennae Search（BAS）. In order to enhance the functional guiding and local searching abilities of AGA, Beetle Antennae Operator（BA） is utilized to improve the new individuals produced by AGA. The data-driven strategy is adopted to reduce the complexity caused by hybridizing of algorithms, and the sensitivity analysis is carried out regarding different dimensional variables with the objective function so as to optimize the evolution path and improve the algorithmic efficiency. The application effect of the algorithm in truss size optimization is studied through quantitative experiments, and the advantages and characteristics of the algorithm are demonstrated through qualitative analysis of the reasons behind the data. The results achieved from the truss size optimization case study show that the lowest economic benefit scheme of steel is 2 490.56 kg, which is consistent with the results from other meta-heuristic algorithms, confirming the accuracy and effectiveness of the proposed BAGA. The average steel amount of 40 000 economic benefit schemes is 2 491.43 kg with the standard deviation 8.05 and the convergence rate 98%, compared with other meta-heuristic algorithms, demonstrating the high stability of BAGA.