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Genetic Algorithms in Application to the Geometry Optimization of Nanoparticles

Middle East Technical University, Department of Physics, Ankara, Turkey
Author to whom correspondence should be addressed.
Algorithms 2009, 2(1), 410-428;
Received: 24 November 2008 / Revised: 6 January 2009 / Accepted: 26 February 2009 / Published: 4 March 2009
(This article belongs to the Special Issue Algorithms and Molecular Sciences)
PDF [597 KB, uploaded 9 March 2009]


Applications of genetic algorithms to the global geometry optimization problem of nanoparticles are reviewed. Genetic operations are investigated and importance of phenotype genetic operations, considering the geometry of nanoparticles, are mentioned. Other efficiency improving developments such as floating point representation and local relaxation are described broadly. Parallelization issues are also considered and a recent parallel working single parent Lamarckian genetic algorithm is reviewed with applications on carbon clusters and SiGe core-shell structures. View Full-Text
Keywords: Genetic algorithms; Nanoparticles; Atomic clusters Genetic algorithms; Nanoparticles; Atomic clusters

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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Dugan, N.; Erkoç, Ş. Genetic Algorithms in Application to the Geometry Optimization of Nanoparticles. Algorithms 2009, 2, 410-428.

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