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Issue 3, 2015
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Pool-BCGA: a parallelised generation-free genetic algorithm for the ab initio global optimisation of nanoalloy clusters

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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.

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

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Publication details

The article was received on 25 Sep 2014, accepted on 01 Dec 2014 and first published on 01 Dec 2014


Article type: Paper
DOI: 10.1039/C4CP04323E
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Phys. Chem. Chem. Phys., 2015,17, 2104-2112
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    Pool-BCGA: a parallelised generation-free genetic algorithm for the ab initio global optimisation of nanoalloy clusters

    A. Shayeghi, D. Götz, J. B. A. Davis, R. Schäfer and R. L. Johnston, Phys. Chem. Chem. Phys., 2015, 17, 2104
    DOI: 10.1039/C4CP04323E

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