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Discrete particle swarm optimization for constructing uniform design on irregular regions
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Discrete particle swarm optimization for constructing uniform design on irregular regions

Ray-Bing Chen, Yen-Wen Hsu, Ying HungWeichung Wang
Computational Statistics and Data Analysis, 卷.72, 頁碼.282-297
04/2014

摘要

Central composite discrepancy Graphic processing unit Non-collapsing Parallel computing Statistics and Probability Computational Mathematics Computational Theory and Mathematics Applied Mathematics
Central composite discrepancy (CCD) has been proposed to measure the uniformity of a design over irregular experimental region. However, how CCD-based optimal uniform designs can be efficiently computed remains a challenge. Focusing on this issues, we proposed a particle swarm optimization-based algorithm to efficiently find optimal uniform designs with respect to the CCD criterion. Parallel computation techniques based on state-of-the-art graphic processing unit (GPU) are employed to accelerate the computations. Several two- to five-dimensional benchmark problems are used to illustrate the advantages of the proposed algorithms. By solving a real application in data center thermal management, we further demonstrate that the proposed algorithm can be extended to incorporate desirable space-filling properties, such as the non-collapsing property. © 2013 Elsevier B.V. All rights reserved.

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