关键词: 遗传算法, 天牛须搜索算法, 杂交算法, 尺寸优化, 灵敏度分析

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.

Key words: genetic algorithm, beetle antennae search algorithm, hybrid algorithm, size optimization, sensitivity analysis