Multi niche crowding genetic algorithm parameter tuning for molecular potential energy surface computation

Article type: Research Article

Authors: El Merbouh, B.^* | El Gridani, A.

Affiliations: Département de Chimie, Faculté des Sciences, Université Ibn Zohr, Agadir, Maroc

Correspondence: [*] Corresponding author: B. El Merbouh, Département de Chimie, Faculté des Sciences, Université Ibn Zohr, B.P. 8106, 80000, Agadir, Maroc. Tel.: +1 514 737 1647; E-mail: elmerbouh@gmail.com.

Abstract: In this paper, we present a Meta genetic algorithm (GA) optimization approach to tune the parameters of the multi niche crowding (MNC) GA, previously used to successfully describe the potential energy surface of different molecular systems at the semi empirical level of theory. The optimization is performed using a second layer of the same algorithm for a set of molecules of different sizes. Several sets of parameters were found that lead to a high performance of the algorithm in terms of the number of the minima found. The variation of the parameters for each molecule is discussed. A relationship between the changes of parameters as a function of the number of degrees of freedom of the molecule has been established.

Keywords: Genetic algorithm, multi-niche crowding, parameter tuning, potential energy surface

DOI: 10.3233/JCM-190026

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 19, no. 4, pp. 1127-1136, 2019