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, R. L. Johnston

Research output: Contribution to journalArticlepeer-review

68 Citations (Scopus)
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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.
Original languageEnglish
Pages (from-to)2104-2112
JournalPhysical Chemistry Chemical Physics
Volume17
Issue number3
Early online date1 Dec 2014
DOIs
Publication statusPublished - 21 Jan 2015

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