基于多目标遗传算法的可调节变量产品族优化

被引:10
作者
李中凯
谭建荣
冯毅雄
魏喆
机构
[1] 浙江大学CAD&CG国家重点实验室
关键词
可调节变量产品族; 产品平台; NSGA-II; 多目标优化; Pareto集;
D O I
暂无
中图分类号
TB497 [技术管理];
学科分类号
08 ;
摘要
为了实现可调节变量产品族的优化设计,在建立可调节变量产品族原理模型及优化模型的基础上,提出基于非支配排序遗传算法(NSGA-II)的产品族优化设计流程.根据产品族优化设计的数学模型,用NSGA-II算法求得多目标优化问题的Pareto集,并使用基于模糊集合理论的方法选择一个最优解.在优化设计的第一阶段中NS-GA-II算法独立优化每个产品,依据设计变量的变化率确定产品平台常量集合及平台常量取值.第二阶段用NS-GA-II算法优化每个实例产品的可调节变量值,在满足产品族设计要求的前提下,提高实例产品的性能.对通用电机产品族进行优化设计,并与One-Stage-Ps方法进行比较,证明了该方法在工程应用中的正确性与高效性.
引用
收藏
页码:1015 / 1020+1057 +1057
页数:7
相关论文
共 12 条
[1]  
Multiobjective function opti mization using nondominated sorting genetic algorithms. Srinivas N,Deb K. Evolutionary Computation . 1995
[2]  
Pareto-optimal solutions for multi-objective optimization of fed-batch bioreactors using nondominated sorting genetic algorithm. Debasis Sarkar and Jayant M. Modak. Chemical Engineering Science . 2005
[3]  
Multiobjective optimization of an industrial grinding operation using elitist nondominated sorting genetic algorithm. Kishalay Mitra and Ravi Gopinath. Chemical Engineering Science . 2004
[4]  
Nondominated sorting genetic algorithm for optimal phasor measurement placement. Milosevic B,Begovic M. IEEE Transactions on Power Systems . 2003
[5]  
A fastand elitist multi-objective genetic algorithm. Deb K,Pratap A,AgarwalS,Meyarivn T1. NS-GA-Ⅱ.IEEE Transactions on Evolutionary Compu-tation . 2002
[6]  
Effective product family designusing preference aggregation. DAI Z H,,SCOTT M J. Proceedings of DECT2004 ASME Design Engineering Technical Conferences . 2004
[7]  
Assessing variable levelsof platform commonality within a product family usingamultiobjective genetic algorithm. SIMPSON T W,BRAYAN D. 9th AIAA/ISSMOSymposium on Multidisciplinary Analysis and Optimiza-tion . 2002
[8]  
Amethodology to support product family redesign using agenetic algorithm and commonality indices. THEVENOT H J,NANDA J,SIMPSON T W. ASME2005 International Design Engineering Technical Confer-ences&Computers and Information in Engineering Con-ference . 2005
[9]  
Multiobjective evolutionary algorithmsfor electric power dispatch problem. ABIDO M A. IEEE Trans-actions on Evolutionary Computation . 2006
[10]  
Product platform design:method and application. Simpson T W,Maier J R A,Mistree F. Research in Engineering Design . 2001