An Efficient Algorithm for Constructing Optimal Design of Computer Experiments
An Efficient Algorithm for Constructing Optimal Design of Computer Experiments
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DOI：
10.1115/detc2003/dac-48760
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发表时间：
2005-09
影响因子：
16.6
通讯作者：
Ruichen Jin;Wei Chen;A. Sudjianto
中科院分区：
文献类型：
--
作者：
Ruichen Jin;Wei Chen;A. Sudjianto
由于在工程设计中使用高保真仿真的高计算成本，元建模方法得到了广泛的应用。元模型的准确性与所使用的实验设计直接相关。最优实验设计已被证明具有良好的“空间填充”和投影特性。然而，建造它们的高成本限制了它们的使用。本文提出了一种构造最优试验设计的新算法。这项工作有两个主要进展。一是提出了一种高效的全局最优搜索算法--增强型随机进化算法。另一个是开发有效的算法来评估最优性标准。所提出的算法相比，现有的两种算法，被发现是更有效的计算时间，产生新的设计所需的交流的数量，并实现最优性标准。该算法也非常灵活，可以构造各种类型的优化设计，以保持某些结构特性。
Metamodeling approach has been widely used due to the high computational cost of using high-fidelity simulations in engineering design. The accuracy of metamodels is directly related to the experimental designs used. Optimal experimental designs have been shown to have good “space filling” and projective properties. However, the high cost in constructing them limits their use. In this paper, a new algorithm for constructing optimal experimental designs is developed. There are two major developments involved in this work. One is on developing an efficient global optimal search algorithm, named as enhanced stochastic evolutionary (ESE) algorithm. The other is on developing efficient algorithms for evaluating optimality criteria. The proposed algorithm is compared to two existing algorithms and is found to be much more efficient in terms of the computation time, the number of exchanges needed for generating new designs, and the achieved optimality criteria. The algorithm is also very flexible to construct various classes of optimal designs to retain certain structural properties.Copyright © 2003 by ASME