An Adaptive Genetic Algorithm for determining optimal structures for atomic clusters

Fuente: arXiv
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Autores principales: Willnecker, Brandon, Moodley, Mervlyn
Formato: Preprint
Publicado: 2024
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author Willnecker, Brandon
Moodley, Mervlyn
author_facet Willnecker, Brandon
Moodley, Mervlyn
contents The implementation of adaptive genetic algorithms (AGA) for optimization problems has proven to be superior than many other methods due to its nature of producing more robust and high quality solutions. Considering the complexity involved in many-body simulations, a novel AGA is proposed for applications to such systems and is specifically used to determine the lowest energy structures of various sized atomic clusters. For demonstrative purposes, we apply our method to various sized Lennard-Jones clusters and show that our results are more accurate than those found in the literature employing different methods.
format Preprint
id arxiv_https___arxiv_org_abs_2411_18087
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle An Adaptive Genetic Algorithm for determining optimal structures for atomic clusters
Willnecker, Brandon
Moodley, Mervlyn
Computational Physics
The implementation of adaptive genetic algorithms (AGA) for optimization problems has proven to be superior than many other methods due to its nature of producing more robust and high quality solutions. Considering the complexity involved in many-body simulations, a novel AGA is proposed for applications to such systems and is specifically used to determine the lowest energy structures of various sized atomic clusters. For demonstrative purposes, we apply our method to various sized Lennard-Jones clusters and show that our results are more accurate than those found in the literature employing different methods.
title An Adaptive Genetic Algorithm for determining optimal structures for atomic clusters
topic Computational Physics
url https://arxiv.org/abs/2411.18087