Optimizing two-level supersaturated designs using swarm intelligence techniques

Frederick Kin Hing Phoa, Ray Bing Chen, Weichung Wang, Weng Kee Wong

研究成果: Article同行評審

19 引文 斯高帕斯(Scopus)


Supersaturated designs (SSDs) are often used to reduce the number of experimental runs in screening experiments with a large number of factors. As more factors are used in the study, the search for an optimal SSD becomes increasingly challenging because of the large number of feasible selection of factor level settings. This article tackles this discrete optimization problem via an algorithm based on swarm intelligence. Using the commonly used E(s2) criterion as an illustrative example, we propose an algorithm to find E(s2)-optimal SSDs by showing that they attain the theoretical lower bounds found in previous literature. We show that our algorithm consistently produces SSDs that are at least as efficient as those from the traditional CP exchange method in terms of computational effort, frequency of finding the E(s2)-optimal SSD, and also has good potential for finding D3-, D4-, and D5-optimal SSDs. Supplementary materials for this article are available online.

頁(從 - 到)43-49
出版狀態Published - 2016 一月 2

All Science Journal Classification (ASJC) codes

  • 統計與概率
  • 建模與模擬
  • 應用數學


深入研究「Optimizing two-level supersaturated designs using swarm intelligence techniques」主題。共同形成了獨特的指紋。