摘要
针对算法收敛速度慢、搜索盲目性大等不足,引入了自适应步长、路径交换邻域搜索和差分进化算法的变异策略,使得改进后的算法收敛性加强,收敛速度提高,改善了随机性,提高了寻优精度;算法到后期搜索平坦化,引入遗传算法中的交叉与变异行为,增加种群多样性,提高了算法的全局稳定性。将改进的算法运用到桥式起重机主梁中进行优化并运用ANSYS进行力学分析,实例检验了算法的可行性;最后通过对比优化前后的结果,得出优化后的主梁质量减重效果明显且符合设计要求,对实际工程结构的设计有指导意义。
On the basis of the basic ABCA for its slow convergence, large Searching blindness and other issues, the introduction of a self-adaptive step length, path exchanging neighborhood search makes the convergence of the improved algorithms to strengthen and improve the convergence speed,the randomness and the optimization accuracy. For a planarization of late algorithm searching, the introduction of crossover and mutation of genetic algorithm, increase the diversity of population, to enhance the global stability of the algorithm. The improved algorithm applied to the main beam of bridge crane and optimized using ANSYS mechanical analysis. An example to verify the feasibility of the algorithm. Finally through the contrast before and after the optimization results that the optimized beam quality and the effect of weight loss significantly and in accordance with design requirements, have directive significance to the actual engineering structure design.
出处
《机械设计与研究》
CSCD
北大核心
2017年第3期99-104,共6页
Machine Design And Research
