Development of a multi-population parallel genetic algorithm for structure solution from powder diffraction data

Scott Habershon, Kenneth Harris, Roy Johnston

Research output: Contribution to journalArticle

60 Citations (Scopus)

Abstract

Previously, the genetic algorithm (GA) approach for direct-space crystal structure solution from powder diffraction data has been applied successfully in the structure determination of a range of organic molecular materials. In this article, we present a further development of our approach, namely a multipopulation parallel GA (PGA), which is shown to give rise to increased speed, efficiency, and reliability of structure solution calculations, as well as providing new opportunities for further optimizing our GA methodology. The multipopulation PGA is based on the independent evolution of different subpopulations, with occasional interaction (e.g., transfer of structures) allowed to occur between the different subpopulations. Different strategies for carrying out this interpopulation communication are considered in this article, and comparisons are made to the conventional single-population GA. The increased power offered by the PGA approach creates the opportunity for structure determination of molecular crystals of increasing complexity. (C) 2003 Wiley Periodicals, Inc.
Original languageEnglish
Pages (from-to)1766-1774
Number of pages9
JournalJournal of Computational Chemistry
Volume24
Issue number14
Early online date3 Sep 2003
DOIs
Publication statusPublished - 15 Nov 2003

Keywords

  • genetic algorithms
  • powder diffraction
  • parallel computing
  • global optimization
  • structure determination

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