An efficient algorithm for constructing optimal design of computer experiments

被引:471
作者
Jin, RC
Chen, W
Sudjianto, A
机构
[1] Northwestern Univ, IDEAL, Evanston, IL 60208 USA
[2] Ford Motor Co, V Engine Engn, Dearborn, MI 48121 USA
基金
美国国家科学基金会;
关键词
optimal design; computer experiments; stochastic evolutionary algorithm;
D O I
10.1016/j.jspi.2004.02.014
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The long computational time required in constructing optimal designs for computer experiments has limited their uses in practice. 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 methods for evaluating optimality criteria. The proposed algorithm is compared to existing techniques and 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 desired structural properties. (c) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:268 / 287
页数:20
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