期刊
COMPUTATIONAL MATERIALS SCIENCE
卷 45, 期 1, 页码 111-117出版社
ELSEVIER
DOI: 10.1016/j.commatsci.2008.03.046
关键词
Genetic algorithm; Alloys; Disordered materials; Surfaces; Monte Carlo; Ising model
We present a genetic algorithm for the atomistic design and global optimisation of substitutionally disordered bulk materials and surfaces. Premature convergence which hamper conventional genetic algorithms due to problems with synchronisation is avoided using a symmetry adapted crossover. The algorithm outperforms previously reported Monte Carlo and genetic algorithm simulations for finding low energy minima of two simple alloy models without the need for any redesign. (C) 2008 Elsevier B.V. All rights reserved.
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