摘要
基于遗传算法的起重机主梁设计存在收敛速度慢、局部最优和早熟收敛等问题。为优化设计方法,对遗传算法中选择算子和变异算子进行了改进与优化,基于生物优胜劣汰的思想上将保留最优个体的方法融入到遗传算法中,保证最优基因能够迅速遗传到后代,加快收敛,同时采取优化变异最优个体的方法,避免了算法落入到局部最优。应用改进遗传算法和周期性拓扑优化设计方法分别完成起重机主梁的优化设计,计算结果表明:改进遗传算法提高了算法的收敛速率和全局收敛能力,优化了起重机主梁设计方法。
In view of the traditional optimization designoptimum and premature convergence problems, a newfor crane girders has slow convergence and localimproved genetic algorithm is proposed for theoptimization design of crane girders. Both the selection operator and the mutation operator in the geneticalgorithm are optimized. The method of reserving the best individual based on the principle of the superiorsurviving is integrated into the frame of the genetic algorithm. The fast transmission of the elitist genes intothe later generation and the increase of the convergence speed are guaranteed. Meanwhile, the mutation ofthe elitist is put forward so as to achieve the global convergence of the algorithm. The optimization results ofthe main beam cross-section for the crane structure from periodic topology optimization and the improvedgenetic algorithm are compared with one another. The comparison analysis indicates that this improvedgenetic algorithm is greatly enhanced in terms of the convergence speed and the global optimality.
出处
《控制工程》
CSCD
北大核心
2017年第7期1415-1418,共4页
Control Engineering of China
基金
杨凌职业技术学院科学研究基金项目(A2015022)
关键词
遗传算法
起重机主梁
优化设计
优化变异
Genetic algorithm
crane girder
optimization design
mutation operator of optimization
