Discrete particle swarm optimization for constructing uniform design on irregular regions

Ray-Bing Chen, Yen-Wen Hsu, Ying Hung and Weichung Wang

Computational Statistics & Data Analysis, 2014, vol. 72, issue C, 282-297

Abstract: 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.

Keywords: Central composite discrepancy; Graphic processing unit; Parallel computing; Non-collapsing (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:72:y:2014:i:c:p:282-297

DOI: 10.1016/j.csda.2013.10.015

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