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 language | English |
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Pages (from-to) | 1766-1774 |
Number of pages | 9 |
Journal | Journal of Computational Chemistry |
Volume | 24 |
Issue number | 14 |
Early online date | 3 Sept 2003 |
DOIs | |
Publication status | Published - 15 Nov 2003 |
Keywords
- genetic algorithms
- powder diffraction
- parallel computing
- global optimization
- structure determination