面向主梁优化的改进果蝇优化算法研究
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摘要
针对果蝇优化算法收敛速度慢、易陷入局部最优、收敛早熟等不足,引入了自适应步长、粒子群算法中的粒子速度,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。将改进果蝇优化算法运用到桥式起重机主梁的轻量化中,并运用有限元软件对优化后的主梁进行力学分析,通过实例验证了算法的优越性;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。
Because the convergence speed of the algorithm is slow and it is easy to fall into local optimization,premature convergence and so on,the adaptive step size and particle velocity in particle swarm optimization algorithm are introduced,thus making the improved algorithm used to improve the convergence,convergence speed,randomness and optimization accuracy. The improved algorithm is applied to the main beam of bridge crane and the finite element software ANSYS is used to do its mechanical analysis. For example,the feasibility of the algorithm is verified. The results before and after the optimization are contrasted. It comes to the conclusion that the optimized beam quality and the effect of weight loss meet the design requirements. It is of directive significance to the actual engineering structure design.
Because the convergence speed of the algorithm is slow and it is easy to fall into local optimization,premature convergence and so on,the adaptive step size and particle velocity in particle swarm optimization algorithm are introduced,thus making the improved algorithm used to improve the convergence,convergence speed,randomness and optimization accuracy. The improved algorithm is applied to the main beam of bridge crane and the finite element software ANSYS is used to do its mechanical analysis. For example,the feasibility of the algorithm is verified. The results before and after the optimization are contrasted. It comes to the conclusion that the optimized beam quality and the effect of weight loss meet the design requirements. It is of directive significance to the actual engineering structure design.
引文
[1]潘文超.应用果蝇优化算法优化广义回归神经网络进行企业经营绩效评估[J].太原理工大学学报(社会科学版),2011,29(4):1-5.
[2]赵静艺.基于果蝇优化算法的混合发电系统最优容量配置[D].长沙:湖南大学,2015.
[3]丁凯.无线传感器网络果蝇路由优化算法研究[D].上海:华东理工大学,2015.
[4]张凯,王健,蒋惠波,等.基于改进果蝇算法的桥式起重机金属结构优化设计[J].起重运输机械,2014(8):41-44.
[5]李志雄,王宗彦,董浩,等.面向主梁优化的改进人工蜂群算法[J].机械设计与研究,2017(3):99-104.
[6]李瑞祥.基于改进人工鱼群算法的桥式起重机主梁优化设计研究[D].太原:中北大学,2015.
[7]候聪亚.基于改进萤火虫算法的桥式起重机主梁优化设计研究[D].太原:中北大学,2015.
[8]潘文超.应用果蝇优化算法优化广义回归神经网络进行企业经营绩效评估[J].太原理工大学学报(社会科学版),2011,29(4):1-5.
[9]陆民迪,周永权,黄慷.一种基于复数编码的果蝇优化算法[J].计算机工程,2015,41(10):181-185.
[10]陆民迪.果蝇优化算法改进与分析研究[D].南宁:广西大学,2015.
[11]韩俊英,刘成忠.自适应变异的果蝇优化算法[J].计算机应用研究,2013,30(9):2641-2644.
[12]张质文,虞和谦,王金诺,等.起重机设计手册[M].北京:中国铁道出版社,2013.
[2]赵静艺.基于果蝇优化算法的混合发电系统最优容量配置[D].长沙:湖南大学,2015.
[3]丁凯.无线传感器网络果蝇路由优化算法研究[D].上海:华东理工大学,2015.
[4]张凯,王健,蒋惠波,等.基于改进果蝇算法的桥式起重机金属结构优化设计[J].起重运输机械,2014(8):41-44.
[5]李志雄,王宗彦,董浩,等.面向主梁优化的改进人工蜂群算法[J].机械设计与研究,2017(3):99-104.
[6]李瑞祥.基于改进人工鱼群算法的桥式起重机主梁优化设计研究[D].太原:中北大学,2015.
[7]候聪亚.基于改进萤火虫算法的桥式起重机主梁优化设计研究[D].太原:中北大学,2015.
[8]潘文超.应用果蝇优化算法优化广义回归神经网络进行企业经营绩效评估[J].太原理工大学学报(社会科学版),2011,29(4):1-5.
[9]陆民迪,周永权,黄慷.一种基于复数编码的果蝇优化算法[J].计算机工程,2015,41(10):181-185.
[10]陆民迪.果蝇优化算法改进与分析研究[D].南宁:广西大学,2015.
[11]韩俊英,刘成忠.自适应变异的果蝇优化算法[J].计算机应用研究,2013,30(9):2641-2644.
[12]张质文,虞和谦,王金诺,等.起重机设计手册[M].北京:中国铁道出版社,2013.