Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm)
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2013-04-15
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Universidade Federal de Goiás
Resumo
This work focuses on the development of the software MGA, which aims to determine
the lowest energy structures of a given molecular system, using Genetic Algorithm (GA).
The GA is a method of artificial intelligence that was developed to work with finding
the best solutions of the specified conditions, ie, an algorithm that seeks the best answer
desired, an optimal result. The MGA uses three techniques: Random Search (RS), Noninclusive Genetic Algorithm (NGA), Inclusive Genetic Algorithm (IGA). The last one is
characterized by a new type of evolutionary strategy that allows in a single calculation
and a single cycle, obtain several minimum of the potential energy surface. For optimum
operation of the algorithm, was made an optimization of the parameters used in
MGA, through response surface methodology. Using the techniques RS, IGA and NGA,
were determined 141 distinct molecular structures of the amino acid asparagine. In the
electronic structure calculations were considered the semi-empirical methods PM3, AM1
and RM1; and DFT potentials, with basis sets 6-311G ** and PC1. The RS determined
the Global Minimum (GM) with ease, for the different potentials used, and proved that
it’s quite useful in determining molecular geometries where there is no accuracy in the
determination of local minima in order of energy. The NGA is efficient in determining the
GM, performing in a shorter time, if compared to RS and IGA. The IGA proved to be a
more robust method than the others, because in addition to determining the GM, it can
find the local minima in order of energy. Performing calculations on an intermediate time
of RS and NGA, the IGA determined the GM as the NGA, and found structures that
were not founded using RS. The GM’s of asparagine determined using the potentials PC1,
PM3, AM1 and RM1 have a large structural difference. This demonstrates that different
potencials used in the electronic structure calculations may lead to different results. By
analyzing the structures obtained for potentials PC1, PM3, AM1 and RM1, using the
IGA, it appears that there is a difference in the topology of the potential energy surface
of these potentials.
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COUTO, R. C. Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm). 2013. 98 f.
Dissertação (Mestrado em Química) - Universidade Federal de Goiás, Goiânia, 2013.