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Erschienen in:
2016 | OriginalPaper | Buchkapitel
On Multiple-Objective Nonlinear Optimal Designs
verfasst von : Qianshun Cheng, Dibyen Majumdar, Min Yang
Erschienen in: mODa 11 - Advances in Model-Oriented Design and Analysis
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Abstract
Experiments with multiple-objectives form a staple diet of modern scientific research. Deriving optimal designs with multiple-objectives is a long-standing challenging problem with few tools available. The few existing approaches cannot provide a satisfactory solution in general: either the computation is very expensive or a satisfactory solution is not guaranteed. There is need for a general approach which can effectively derive multi-objective optimal designs. A novel algorithm is proposed to address this literature gap. We prove convergence of this algorithm, and show in various examples that the new algorithm can derive the true solutions with high speed.