中国机械工程 ›› 2011, Vol. 22 ›› Issue (20): 2428-2436.

• 信息技术 • 上一篇    下一篇

无公用平台下的参数化产品族多目标智能优化

单汨源1;王克喜1,2;袁际军3
  

  1. 1.湖南大学,长沙,410082
    2.湖南科技大学,湘潭,411201
    3.广东商学院,广州,510320
  • 出版日期:2011-10-25 发布日期:2011-11-02
  • 基金资助:
    国家自然科学基金资助项目(70971036,71102146)
    National Natural Science Foundation of China(No. 70971036,71102146)

Multi-objective Intelligence Optimization for Scale-based Product Family without Platform Commonality

Shan Miyuan1;Wang Kexi1,2;Yuan Jijun3
  

  1. 1.Hunan University,Changsha,410082
    2.Hunan University of Science and Technology,Xiangtan,Hunan,411201
    3.Guangdong University of Business Studies,Guangzhou,510320
  • Online:2011-10-25 Published:2011-11-02
  • Supported by:
    National Natural Science Foundation of China(No. 70971036,71102146)

摘要:

在忽略产品间共性约束的条件下,参数化产品族整体性能的优化实际上等价于产品族内系列产品的独立优化。基于参数化产品族优化问题的复杂性,提出了一种基于拥挤距离排序的多目标多约束遗传算法(CDSMOGA),并将其用于求解无公用平台下的产品族优化问题。通用电动机产品族设计实例的仿真试验结果表明,CDSMOGA所得产品族优化设计方案整体性能显著优于被比较方案,验证了该方法的有效性和可行性。

关键词:

Abstract:

Without regard for commonality among products,an optimization of scale-based product family was equivalent to the optimization of the product in the family independently.Considering the complexity of optimization design of product family,CDSMOGA,a multi-objective genetic algorithm based on crowding distance sorting was proposed to solve the optimization problem of product family.The feasibility and effectiveness of proposed CDSMOGA were demonstrated by the optimization design of universal motor families. The simulation experiments also show that the whole performances of universal motor families obtained from CDSMOGA are evidently better than that in the previous literatures.

Key words: mass customization, scale-based product family, multi-objective optimization, genetic algorithm, crowding distance sorting

中图分类号: