基于两种效应的RSM多响应优化方法研究
首发时间:2018-05-15
摘要:在多响应优化问题研究中,权衡响应的位置效应与分散效应是十分重要的内容。本文提出了基于响应的位置与分散效应构建的损失函数方法,在考虑多响应间相关性的情况下,权衡位置与分散效应的相对重要性,以获得符合试验者期望的最优输入因子组合。此外,本文同时允许试验者对比不同权重水平下响应位置效应与分散效应的损失水平及变化趋势,从而为其遴选出最理想的输入因子组合提供有效信息。实例分析结果表明,在多响应优化问题中,本文方法适用于更多实际情境,且更为有效。
关键词: 生产与质量管理 响应曲面优化 多响应 相关性 分散效应 损失函数
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Evaluate Location and Dispersion Effects in Multiresponse Optimization when Correlations Considered
Abstract:Location and dispersion effects play different roles in a multiresponse problem, therefore, balancing them at different levels in the optimization process is an important and challenging topic for any designers. In this paper, we propose to use loss function tackling the relative importance of the location and dispersion effects simultaneously, at the same time considering the responses’ correlations. Instead of fixing the relationship between the location and dispersion effects, our approach works out more compromise solutions versus their relative importance. which allows for a flexible choice when designers balancing the location and dispersion effects for multiple responses. Examples are used to furtherly illustrate its advantages.
Keywords: quality management response surface methodology multiresponse optimization correlations dispersion effect loss function
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基于两种效应的RSM多响应优化方法研究
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