Pool-BCGA: a parallelised generation-free genetic algorithm for the ab initio global optimisation of nanoalloy clusters

Literature Information

Publication Date 2014-12-01
DOI 10.1039/C4CP04323E
Impact Factor 3.676
Authors

A. Shayeghi, D. Götz, J. B. A. Davis, R. Schäfer, R. L. Johnston


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Abstract

The Birmingham cluster genetic algorithm is a package that performs global optimisations for homo- and bimetallic clusters based on either first principles methods or empirical potentials. Here, we present a new parallel implementation of the code which employs a pool strategy in order to eliminate sequential steps and significantly improve performance. The new approach meets all requirements of an evolutionary algorithm and contains the main features of the previous implementation. The performance of the pool genetic algorithm is tested using the Gupta potential for the global optimisation of the Au10Pd10 cluster, which demonstrates the high efficiency of the method. The new implementation is also used for the global optimisation of the Au10 and Au20 clusters directly at the density functional theory level.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
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