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標題: 透過群聚智能演算法建構最佳貝氏D準則交錯式層級超飽和實驗設計
Via Swarm Intelligence Construct the Bayesian D-Optimal Staggered-Level Supersaturated Designs
作者: 吳豪翔
Hao-Siang Wu
關鍵字: 超飽和實驗設計;交錯式層級設計;貝氏D準則;平衡設計;縱列的成對互換演算法;Supersaturated designs;Staggered-level designs;Bayesian D criterion;Balanced designs;Columnwise-pairwise algorithm
引用: Arnouts, H.; Goos, P. (2012). Staggered-level Designs for Experiments with More than One Hard-to-Change Factor. Technometrics, 54, 355-366. Booth, K.H.V.; Cox, D.R. (1962). Some Systematic Supersaturated Designs. Technometrics, 4, 489-495. Dumouchel, W.; Jones, B. (1994). A Simple Bayesian Modification of D-Optimal Designs to Reduce Dependence on an Assumed Model. Technometrics, 36, 37-47. Fisher, R.A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. Jones, B.; Lin, D.K.J.; Nachtsheim, C.J. (2008). Bayesian D-optimal Supersaturated Designs. Journal of Statistical Planning and Inference, 138, 86-92. Li, W.W.; Wu, J.C.F. (1997). Columnwise-Pairwise Algorithms with Applications to the Construction of Supersaturated Designs. Technometrics, 39, 171-179. Lin, C.Y. (2014). Optimal Blocked Orthogonal Arrays. Journal of Statistical Planning and Inference, 145, 139-147. Lin, C.Y. (2015). Construction and Selection of the Optimal Balanced Blocked Definitive Screening Design. Metrika, 78, 373-383. Lin, C.Y. (2017). Supersaturated Multistratum Designs. Journal of Quality Technology, In press. Lin, C.Y. (2018a). Generalized Bayesian D criterion for Single-Stratum and Multistratum Designs. Quality and Reliability Engineering international, DOI: 10.1002/qre.2335. Lin, C.Y. (2018b). Robust Designs with High Projection Efficiency. Quality and Reliability Engineering international, 34, 347-359. DOI: 10.1002/qre.2257. Lin, C.Y. (2018c). Robust Split-Plot Designs for Model Misspecification. Journal of Quality Technology, 50, 76-87. Lin, C.Y.; Yang P. (2015). Response Surface Methodology Using split-plot Definitive Screening Designs. Journal of Quality Technology, 47, 351-362. Lin, C.Y.; Yang P. (2018). Robust Multistratum Baseline Designs. Computational Statistics and Data Analysis, 118, 98-111. Lin, C.Y.; Yang P.; Cheng S.W. (2017). Minimum Contamination and Beta-Aberration Criteria for Screening Quantitative Factors. Statistica Sinica, 27, 607-623. Meyer, R.K.; Nachtsheim, C.J. (1995). The Coordinate-Exchange Algorithm for Constructing Exact Optimal Experimental Designs. Technometrics, 37, 60-69. Miller, A. (1997). Strip-Plot Configurations of Fractional Factorials. Technometrics, 39, 153-161. Phoa, F.K.H.; Chen, R.B.; Wang, W.; Wong, W.K. (2016). Optimizing Two-level Supersaturated Designs Using Swarm Intelligence Techniques. Technometrics, 58, 43-49. Satterthwaite, F.E. (1959). Random Balance Experimentation. Technometrics, 1, 111-137. Wu, C.F.J. (1993). Construction of Supersaturated Designs Through Partially Aliased Interactions. Biometrika, 80, 661-669. Wu, C.F.J.; Hamada, M. (2000). Experiments: Planning, Analysis, and Parameter Design Optimization. New York: Wiley. Yang, P.; Lin, C.Y.; Li, W. (2015). Blocked Semifoldovers of Two-level Orthogonal Designs. Metrika, 78, 529-548. Yang, P.; Lin, C.Y. (2017). Optimal Split-Plot Orthogonal Arrays. Australian and New Zealand Journal of Statistics, 59, 81-94.

Industrial experiments have many constraints. For instance, there are too many factors for screening or there exist some factors whose levels are not easy to change. In this research, we combine supersaturated designs and staggered-level designs. We use the Bayesian D-optimal criterion and the swarm intelligence techniques to construct our designs.
Rights: 同意授權瀏覽/列印電子全文服務,2018-07-16起公開。
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