A Neural-Network Controlled Dynamic Evolutionary Scheme for Global Molecular Geometry Optimization

Authors:
Anna Styrcz;Janusz Mrozek;Grzegorz Mazur
Affiliations:
Department of Computational Methods in Chemistry, Jagiellonian University, ul. R. Ingardena 3, 30-060 Cracow, Poland;Department of Computational Methods in Chemistry, Jagiellonian University, ul. R. Ingardena 3, 30-060 Cracow, Poland;Department of Computational Methods in Chemistry, Jagiellonian University, ul. R. Ingardena 3, 30-060 Cracow, Poland
Venue:
International Journal of Applied Mathematics and Computer Science - Issues in Advanced Control and Diagnosis
Year:
2011

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Abstract

A novel, neural network controlled, dynamic evolutionary algorithm is proposed for the purposes of molecular geometry optimization. The approach is tested for selected model molecules and some molecular systems of importance in biochemistry. The new algorithm is shown to compare favorably with the standard, statically parametrized memetic algorithm.