Molecular parameter optimization using simulated annealing and evolutionary algorithm techniques in a quantum parametric method (CATIVIC)

Abstract

Application of simulated annealing (SA) and evolutionary algorithm (EA) techniques for optimization of parameters in the parametric quantum chemistry method (CATIVIC) was performed. A set of organic molecules and gold clusters were selected for test these techniques. Comparison was performed with respect to experimental values and DFT calculated equilibrium bond distances (EBD) and bond angles (BA). Results show that EA is more efficient than SA with respect to computer time. Accuracy is similar in both methods; however, there are important differences in the set of parameters.

Keywords:

• Parametric methods
• Simulated annealing
• Evolutionary algorithm
• Global minimum
• Parameterization

Acknowledgements

This research has also been sponsored by FONACIT, Venezuela, under the G-9700667 contract.