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Algorithms 2009, 2(1), 410-428; doi:10.3390/a2010410

Genetic Algorithms in Application to the Geometry Optimization of Nanoparticles

Middle East Technical University, Department of Physics, Ankara, Turkey
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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)
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Abstract

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.
Keywords: Genetic algorithms; Nanoparticles; Atomic clusters Genetic algorithms; Nanoparticles; Atomic clusters
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

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

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