Optimal Sliced Latin Hypercube Designs with Slices of Arbitrary Run Sizes

Jing Zhang, Jin Xu, Kai Jia, Yimin Yin and Zhengming Wang
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Jing Zhang: College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410072, China
Jin Xu: College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410072, China
Kai Jia: College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410072, China
Yimin Yin: College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410072, China
Zhengming Wang: College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410072, China

Mathematics, 2019, vol. 7, issue 9, 1-16

Abstract: Sliced Latin hypercube designs (SLHDs) are widely used in computer experiments with both quantitative and qualitative factors and in batches. Optimal SLHDs achieve better space-filling property on the whole experimental region. However, most existing methods for constructing optimal SLHDs have restriction on the run sizes. In this paper, we propose a new method for constructing SLHDs with arbitrary run sizes, and a new combined space-filling measurement describing the space-filling property for both the whole design and its slices. Furthermore, we develop general algorithms to search for the optimal SLHD with arbitrary run sizes under the proposed measurement. Examples are presented to illustrate that effectiveness of the proposed methods.

Keywords: computer experiment; optimal design; space-filling design; maximin distance criterion (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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