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单平台下参数化产品族设计的两阶段智能优化算法

A Two-stage Multi-objective Intelligent Optimization Algorithm for Single Platform Based Product Family Design
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摘要 基于对参数化产品族优化设计问题特性的分析,提出了单平台下参数化产品族的两阶段优化设计方法。针对单平台产品族优化设计的特征,给出了单平台下参数化产品族优化设计的一般数学模型,在此基础上提出了平台变量值预先设定时的产品族优化模型,给出了采用拥挤距离排序的多目标约束遗传算法(CDSMOGA)对该模型进行优化求解的过程。对单平台下平台变量值已知时的通用电动机产品族优化数学模型进行了仿真运算。对比仿真结果与国内外文献中的相关结果发现,所提出的方法能够显著改善产品族的整体性能,在参数化产品族的优化设计上是有效的。 According to analyses of multi-objective optimization problem for single platform based product family,a two-stage method for the optimization problem of product family was proposed.Based on the model of the optimization problem of single platform product family,an optimization model and the procedure to solve this model,CDSMOGA（crowding distance sorting multi-objective genetic algorithm） was given.The simulation experiments also show that the results obtained from platform variables values without setting in advance during the process of corresponding algorithm running are better than that of platform variables values setting in advance.However,the former has a higher computational complexity.
作者 王克喜 袁际军 陈为民 全春光
机构地区 湖南科技大学 广东商学院
出处 《中国机械工程》 EI CAS CSCD 北大核心 2011年第17期2097-2103,共7页 China Mechanical Engineering
基金 国家自然科学基金资助项目(70971036 70671037) 湖南省哲学社会科学规划项目(08YBB282)
关键词 参数化产品族 多目标优化 遗传算法 拥挤距离排序 scale-based product family multi-objective optimization genetic algorithm crowding distance sorting
分类号 TH122 [机械工程—机械设计及理论]
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参考文献14

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中国机械工程
2011年 第17期

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