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Pool-BCGA:一种用于纳米合金团簇从头全局优化的并行无生成遗传算法。

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

作者信息

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

机构信息

Eduard-Zintl-Institut, Technische Universität Darmstadt, Alarich-Weiss-Straße 8, 64287 Darmstadt, Germany.

出版信息

Phys Chem Chem Phys. 2015 Jan 21;17(3):2104-12. doi: 10.1039/c4cp04323e. Epub 2014 Dec 8.

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.

摘要

伯明翰簇遗传算法是一个基于第一性原理方法或经验势对单金属和双金属簇进行全局优化的软件包。在此,我们展示了该代码的一种新的并行实现方式,它采用了一种池策略来消除顺序步骤并显著提高性能。新方法满足进化算法的所有要求,并包含了先前实现方式的主要特征。使用古普塔势对Au10Pd10簇进行全局优化来测试池遗传算法的性能,这证明了该方法的高效性。新的实现方式还直接在密度泛函理论水平上用于Au10和Au20簇的全局优化。

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