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Inexact genetic algorithm approach to target values setting of engineering requirements in QFD

机译:QFD中工程需求目标值设定的不精确遗传算法

摘要

In Quality Function Deployment, determination of the target values for engineering requirements is the most difficult process. A fuzzy optimization model is presented for the determination of target values for engineering requirements in Quality Function Deployment. An inexact genetic algorithm approach was introduced to solve the model that takes the mutation along the weighted gradient direction as a genetic operator. Instead of obtaining one set of exact optimal target values, the approach can generate a family of inexact optimal target values setting within an acceptable satisfaction degree. Through an interactive approach, a design team can determine a combination of preferred solution sets from which a set of preferred target values of engineering requirements based on a specific design scenario can be obtained. An example of car door design is used to illustrate the approach.
机译:在质量功能部署中,确定工程要求的目标值是最困难的过程。提出了一种模糊优化模型,用于确定质量功能部署中工程要求的目标值。引入了一种不精确的遗传算法方法来求解以加权梯度方向上的突变为遗传算子的模型。代替获得一组精确的最佳目标值,该方法可以生成在可接受的满意度内的一系列不精确的最佳目标值设置。通过交互式方法,设计团队可以确定首选解决方案集的组合,从中可以获得基于特定设计方案的一组工程需求的首选目标值。车门设计的一个示例用于说明该方法。

著录项

  • 作者

    Bai H; Kwong CK;

  • 作者单位
  • 年度 2003
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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