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Constructing General Orthogonal Fractional Factorial Split-Plot Designs

机译:构造通用正交分数阶因子分解图设计

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摘要

While the orthogonal design of split-plot fractional factorial experiments has received much attention already, there are still major voids in the literature. First, designs with one or more factors acting at more than two levels have not yet been considered. Second, published work on nonregular fractional factorial split-plot designs was either based only on Plackett-Burman designs, or on small nonregular designs with limited numbers of factors. In this article, we present a novel approach to designing general orthogonal fractional factorial split-plot designs. One key feature of our approach is that it can be used to construct two-level designs as well as designs involving one or more factors with more than two levels. Moreover, the approach can be used to create two-level designs that match or outperform alternative designs in the literature, and to create two-level designs that cannot be constructed using existing methodology. Our new approach involves the use of integer linear programming and mixed integer linear programming, and, for large design problems, it combines integer linear programming with variable neighborhood search. We demonstrate the usefulness of our approach by constructing two-level split-plot designs of 16-96 runs, an 81-run three-level split-plot design, and a 48-run mixed-level split-plot design. Supplementary materials for this article are available online.
机译:尽管分裂图分数阶乘实验的正交设计已受到广泛关注,但文献中仍存在主要空白。首先,尚未考虑具有一个或多个因素作用于两个以上级别的设计。其次,已发表的关于非常规分数阶因子分解图设计的工作要么仅基于Plackett-Burman设计,要么基于因子数量有限的小型非常规设计。在本文中,我们提出了一种设计一般正交分数阶因子分解图设计的新颖方法。我们方法的一个关键特征是,它可以用于构建两级设计以及涉及一个或多个因素且具有两个以上级的设计。此外,该方法可用于创建与文献中的替代设计相匹配或胜过替代设计的两层设计,以及用于创建无法使用现有方法构建的两层设计。我们的新方法涉及整数线性规划和混合整数线性规划的使用,并且对于大型设计问题,它将整数线性规划与变量邻域搜索相结合。我们通过构造16-96运行的两级拆分图设计,81运行的三级拆分图设计和48运行的混合级拆分图设计来证明我们的方法的有效性。可在线获得本文的补充材料。

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