Title: Genetic operators' significance assessment in multi-population genetic algorithms

Authors: Maria Angelova; Tania Pencheva

Addresses: Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 105 Acad. G. Bonchev Str., 1113 Sofia, Bulgaria ' Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 105 Acad. G. Bonchev Str., 1113 Sofia, Bulgaria

Abstract: Genetic algorithms are widely applied bioinspired optimisation technique that search for a global optimal solution via three main genetic operators, namely selection, crossover, and mutation. In order to determine the operators importance when multi-population genetic algorithm is applied for parameter identification of S. cerevisiae fed-batch cultivation, recently presented procedure for significance assessment has been implemented. Based on obtained results the most significant genetic operator has been distinguished and its influence on finding the global optimal solution has been evaluated as well.

Keywords: multi-population genetic algorithms; genetic operators; parameter identification; S. cerevisiae fed-batch cultivation.

DOI: 10.1504/IJMHEUR.2014.063146

International Journal of Metaheuristics, 2014 Vol.3 No.2, pp.162 - 173

Received: 05 Oct 2013
Accepted: 28 Mar 2014
Published online: 25 Jul 2014 *

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