在存在噪声变量时,对多重响应表面优化的贝叶斯方法
Guillermo Miró-Quesada1, Enrique Del Castillo1,2, John J Peterson2
1Department of Industrial & Manufacturing Engineering, Penn State University, PA, USA.
本研究引入了贝叶斯的方法,用于强大的参数设计,优化流程,以满足多个响应约束,尽管噪声变化. 一种新的方法有效地找到强大的解决方案,增强制造和工程应用.
科学领域:
- 工程 工程师 工程师 工程师
- 统计 统计 统计 统计
- 运营研究 运营研究
背景情况:
- 传统的参数设计与多个响应约束和噪声变化性作斗争.
- 现有的方法可能无法充分解决复杂系统中的稳定性问题.
- 彼得森 (2000年) 的方法提供了强大的设计的基础.
研究的目的:
- 介绍一个贝叶斯的方法,多重响应强大的参数设计问题.
- 开发一种最大化满足响应约束的后置预测概率的方法.
- 为了确保解决方案对噪声变量的变化具有稳定性.
主要方法:
- 贝叶斯框架最大化了限制满足的后置预测概率.
- 对响应和噪声变量进行预测密度的整合,以获得稳定性.
- 评估两种方法来解决涉及蒙特卡洛集成的最大化问题.
主要成果:
- 成功开发了一种用于强大的参数设计的新方法.
- 马特拉布代码可以快速识别最佳,强大的解决方案.
- 该方法通过使用现有文献中的两个说明性示例来验证.
结论:
- 提出的贝叶斯方法有效地解决了多重响应强大的参数设计.
- 通过对噪声变量进行整合,提高了解决方案的稳定性.
- 开发的计算工具促进了强大的设计方法的实际应用.
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