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

Genetic Algorithms in Application to the Geometry Optimization of Nanoparticles

Nazım Duganemail and Şakir Erkoç* email
Middle East Technical University, Department of Physics, Ankara, Turkey
* Author to whom correspondence should be addressed.
Received: 24 November 2008; in revised form: 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

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Cite This Article

MDPI and ACS Style

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

AMA Style

Dugan N, Erkoç Ş. Genetic Algorithms in Application to the Geometry Optimization of Nanoparticles. Algorithms. 2009; 2(1):410-428.

Chicago/Turabian Style

Dugan, Nazım; Erkoç, Şakir. 2009. "Genetic Algorithms in Application to the Geometry Optimization of Nanoparticles." Algorithms 2, no. 1: 410-428.

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