• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2016, Vol. 52 ›› Issue (24): 80-87.doi: 10.3901/JME.2016.24.080

• 仪器科学与技术 • 上一篇    下一篇

具有二重机制的生物地理优化算法及圆柱度 误差评定研究*

鲁宇明1,2,3, 王彦超2, 吴竹溪2   

  1. 1. 南昌航空大学江西省图像处理与模式识别重点实验室 南昌 330063
    , 2. 南昌航空大学航空制造学院 南昌 330063
    , 3. 耶鲁大学医学院 康涅狄格纽黑文 06511 美国
  • 出版日期:2016-12-15 发布日期:2016-12-15
  • 作者简介:

    鲁宇明(通信作者),女,1969年出生,博士,教授。主要研究方向为进化计算及应用、模式识别。

    E-mail:luyuming69@163.com

  • 基金资助:
    * 国家自然科学基金(51465045,61262019)、江西省自然科学基金(20151BAB207065)、江西省科技支撑(20151BBE50069)、深圳市科创委基础研究(JCYJ20140509174140668)、江西省图像处理与模式识别重点实验室开放基金(第三批)和2014国家留学基金委国外访学资助项目; 20160222收到初稿,20161011收到修改稿;

Cylindricity Error Evaluation Based on an Improved Biogeography-based Optimization Algorithm

LU Yuming1,2,3, WANG Yanchao2, WU Zhuxi2   

  1. 1. Key Laboratory of Image Processing and Pattern Recognition in Jiangxi Province, Nanchang Hangkong University, Nanchang 330063
    , 2. College of Aeronautical Manufacturing Engineering, Nanchang Hangkong University, Nanchang 330063
    , 3. School of Medicine, Yale University, Newhaven 06511, USA
  • Online:2016-12-15 Published:2016-12-15

摘要:

生物地理学优化算法(Biogeography-base optimization, BBO)是一种新型的智能算法,因其参数少、易于实现等优点而受到学界的广泛关注和研究,并显示出了广阔的应用前景。为了提高算法的优化性能,对BBO算法提出一种改进。改进的算法在将差分优化算法(Differential evolution, DE)中的局部搜索策略同BBO算法中的迁移策略相结合的基础上,针对迁移算子和变异算子分别做出改进,并通过基准函数的测试证明了改进后的算法在迭代过程中种群进化、寻优能力以及算法的收敛性能得到进一步提升。尝试将改进了的生物地理学优化算法应用于圆柱度误差评定。依据国家标准,结合最小区域法,以圆柱度误差数学模型为目标函数,该算法实现了误差评定优化求解。通过该寻优结果与其他方法的评定结果的比较,验证了该种算法的可行性和正确性及其优越性。

关键词: 差分优化算法, 圆柱度误差评定, 最小区域法, 生物地理学优化算法

Abstract:

The biogeography-based optimization algorithm(BBO) is a new intelligent algorithm. It receives wide academic attention and research, and showed a broad application in many fields. In order to improve the performance of the algorithm, an improved BBO algorithm is proposed, which is based on the combination of the local search strategy in differential evolution(DE) algorithm and the migration strategy in BBO algorithm. The improvement of the migration operator and mutation operator make the evolution and the optimization of the algorithm much better. Meanwhile, the research attempts to apply the improved biogeography optimization algorithm to the cylindricity error evaluation. The process of optimization combines the minimum zone method, according to the national standard, to achieve the purpose of the optimization of the cylindricity error mathematical model of objective function. The results gotten from experiments on the objective function optimization and the results from other methods are compared, which verifies the feasibility of the method and the correctness and superiority.

Key words: cylindricity error evaluation, differential evolution, minimum zone method, biogeography-based optimization algorithm