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无公用平台下的参数化产品族多目标智能优化!

Multi-objective Intelligence Optimization for Scale-based Product Family without Platform Commonality
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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。 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,CDSMOOA,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.
出处 《中国机械工程》 EI CAS CSCD 北大核心 2011年第20期2428-2436,共9页 China Mechanical Engineering
基金 国家自然科学基金资助项目(70971036 71102146)
关键词 大批量定制 参数化产品族 多目标优化 遗传算法 拥挤距离排序 mass customization scale-- based product family multi- objective optimization genet-ic algorithm crowding distance sorting
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