An algorithm for fast optimal Latin hypercube design of experiments

By Felipe Antonio Chegury Viana, Gerhard Venter, Vladimir Balabanov. 2010

340 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ac76b98fea541810da60d546d5e4db2a27948848

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Jianfei Cai
2. Haitao Liu
3. Yew-Soon Ong
4. Xiaofang Wang
5. Haitao Liu
6. Ying Ma
7. Shengli Xu
8. Ferrante Neri

In Management Science and Operations Research

1. Yew-Soon Ong
2. Jianfei Cai
3. Xiaofang Wang
4. Haitao Liu
5. Haitao Liu
6. Ying Ma
7. Shengli Xu

In Statistics and Probability

1. Yew-Soon Ong
2. Jianfei Cai
3. Haitao Liu
4. Shengli Xu

Citations in the corpus

• A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design (2017, methodology): “To further alleviate the optimization budget, a near-optimal LHD is achieved by the translational propagation idea (Viana et al. 2010b; Pan et al. 2014a).”
• Global optimization of expensive black box functions using potential Lipschitz constants and response surfaces (2015, positive): “This article employs the translational propagationlatinhypercubedesign(TPLHD)[42]approachtogeneratetheinitialpointssince thisapproachgeneratespointswithbothspace-fillingandprojectivepropertiesefficiently.”