CONSTRUCTING MIXED-LEVEL SUPERSATURATED DESIGNS BY TWO-STAGE OPTIMIZATION TECHNIQUE

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  • Ohno Takanori
    Graduate School of Science and Engineering, Saitama University:(Present office)Fuji Xerox Co., Ltd.
  • Hashiguchi Hiroki
    Graduate School of Science and Engineering, Saitama University
  • Yamada Shu
    Graduate School of Business Sciences, University of Tsukuba

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  • 二段階最適化法による混合水準過飽和計画の構成
  • 2ダンカイ サイテキカホウ ニ ヨル コンゴウ スイジュン カホウワ ケイカク ノ コウセイ

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Abstract

Supersaturated designs are fractional factorial designs in which the number of columns is greater than or equal to the number of runs. They are helpful when the number of factors to be assigned in an experiment is large, for example, when screening to find a few active factors from many candidates in the primary stage of a scientific investigation and product development. There are several theoretical and computational approaches to construct supersaturated designs, such as random balance design, application of BIBD, algorithmic approach including permutation of rows and columns and so forth. This paper constructs supersaturated designs by an application of random generation and swap method as a two-stage optimization technique. The first stage intends to minimize the total dependency of all paired columns by applying the random generation. The second stage swaps some elements in columns based on the coincidence numbers of rows. The constructed designs are compared with the previous studies by numerical examples. It is demonstrated that the proposed designs have advantages in terms of low-dependency measured by χ^2 values comparing with the previous studies.

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