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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.
|Journal||Physical Chemistry Chemical Physics|
|Early online date||1 Dec 2014|
|Publication status||Published - 21 Jan 2015|
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- 1 Finished
MidPlus: A Centre of Excellence for Computational Science, Engineering and Mathematics - via Warwick
Engineering & Physical Science Research Council
1/01/12 → 31/03/12
Project: Research Councils