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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Chem. | doi: 10.3389/fchem.2019.00707

A new genetic algorithm approach applied to atomic and molecular cluster studies

Frederico T. Silva1, Mateus X. Silva2 and  Jadson C. Belchior2*
  • 1Federal University of Pernambuco, Brazil
  • 2Federal University of Minas Gerais, Brazil

A new procedure is suggested to improve genetic algorithms for the prediction of structures of nanoparticles. The strategy focuses on managing the creation of new individuals by evaluating the efficiency of operators (o1, o2, ..., o13) in generating well-adapted offspring. This is done by increasing the creation rate of operators with better performance and decreasing that rate for the ones which poorly fulfill the task of creating favorable new generation. Additionally, several strategies (thirteen at this level of approach) from different optimization techniques were implemented on the actual genetic algorithm. Trials were performed on the general case studies of 26 and 55-atom clusters with binding energy governed by a Lennard-Jones empirical potential with all individuals being created by each of the particular thirteen operators tested. Results show that our management strategy could avoid bad operators, keeping the overall method performance with great confidence. Moreover, amongst the operators taken from the literature and tested herein, the genetic algorithm was faster when the generation of new individuals was carried out by the twist operator, even when compared to commonly used operators such as Deaven and Ho cut-and-splice crossover. Operators typically designed for basin-hopping methodology also performed well on the proposed genetic algorithm scheme.

Keywords: Cluster optimization, Quantum Genetic Algorithm (QGA), Evolutionary Operator Management, Lennard-Jones clusters, Polynitrogen structure optimization

Received: 05 Jun 2019; Accepted: 09 Oct 2019.

Copyright: © 2019 Silva, Silva and Belchior. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Jadson C. Belchior, Federal University of Minas Gerais, Belo Horizonte, 31270-901, Minas Gerais, Brazil,