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Generating sequential space-filling designs using genetic algorithms and Monte Carlo methods

Authors
  • Crombecq, Karel
  • Dhaene, Tom
Publication Date
Jan 01, 2010
Identifiers
DOI: 10.1007/978-3-642-17298-4_8
OAI: oai:archive.ugent.be:1140796
Source
Ghent University Institutional Archive
Keywords
Language
English
License
White
External links

Abstract

In this paper, the authors compare a Monte Carlo method and an optimization-based approach using genetic algorithms for sequentially generating space-filling experimental designs. It is shown that Monte Carlo methods perform better than genetic algorithms for this specific problem.

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