A fast optimal Latin hypercube design method using an improved translational propagation algorithm. Issue 7 (2nd July 2020)

• Record Type: Journal Article
• Authors: Sun, Yibo; Meng, Xiuyun; Long, Teng; Wu, Yufei
• Is Part Of: Engineering optimization. Volume 52:Issue 7(2020)
• Page Start: 1244
• Page End: 1260
• Publication Date: 2020-07-02
• Subjects: Design of computer experiments -- experimental design -- Latin hypercube sampling -- translational propagation algorithm; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2019.1642881
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: To further improve the space-filling quality and computational efficiency of the translational propagation algorithm, especially for high-dimensional and large-scale sampling problems, this article presents an improved translational propagation algorithm (iTPA). First, a novel uniform translating process is proposed to better allocate sample points. Second, the resizing process is improved to relieve its adverse influence on the space-filling quality. Comparative studies demonstrate the appealing merits of iTPA: (i) iTPA generally outperforms the existing optimization-based Latin hypercube design (LHD) methods; (ii) for high-dimensional and large-scale sampling problems, the computational efficiency of iTPA is dramatically improved and insensitive to sampling dimension and scale; (iii) iterations of iTPA can be used to enrich available LHDs and further upgrade the space-filling quality. Finally, an engineering example is presented to demonstrate the benefit of iTPA in improving the accuracy of surrogates.