摘要
针对云量子遗传算法早熟收敛、搜索速度慢等缺陷,进行如下改进:对量子染色体编码初始化进行优化,使算法拥有更高的收敛性;采用X条件云发生器改变交叉和变异方式实现染色体重构及算子生成;对旋转量子门进行动态调整;结合优化对象改进了算法收敛准则。为验证改进算法以及实现桥式起重机主梁快速设计,以改进算法为优化核心搭建了桥式起重机主梁快速轻量化设计系统,将系统应用于某公司QD型桥式起重机主梁设计,结果表明:所搭建系统可大大缩短桥式起重机主梁优化的设计周期,优化后主梁截面积满足设计要求,实现了主梁快速轻量化设计的目标。
Aiming at the overcome premature convergence and slow search speed in the cloud quantum genetic algorithm,it presents the following improvements:it optimizes the initialization of quantum chromosome coding to make the algorithm have higher convergence,uses X-conditional cloud generator to change the way of crossover and takes the mutation to realize chromosome reconstruction and operator generation.The convergence criterion of the algorithm is improved with the optimization object.A rapidly lightweight design system for the main girder is built with the improved algorithm as the optimization core.The results show that the improved algorithm is superior to other design schemes in lightweight,and the system can greatly shorten the developing cycle of optimization,the optimized section area of the main girder can meet the design requirements,and achieve the goal of rapidly lightweight design of the main girder.
作者
刘岩松
王宗彦
石瑞敏
李玉虎
Liu Yansong;Wang Zongyan;Shi Ruimin;Li Yuhu(School of Mechanical Engineering,North University of China,Shanxi Taiyuan,030051,China;Crane Digital Design Engineering Technology Research Center of Shanxi Province,Shanxi Taiyuan,030051,China)
出处
《机械设计与制造工程》
2020年第1期25-29,共5页
Machine Design and Manufacturing Engineering
关键词
起重机
主梁
改进云量子遗传算法
轻量化设计
crane
main girder
improved cloud quantum genetic algorithm
lightweight design
