Assisted recombination: accelerating genetic improvements of populations in a GA

Authors:
Celso G. Camilo, Jr.;Keiji Yamanaka
Affiliations:
Federal University of Grande Dourados, Dourados, MS, Brasil;Federal University of Uberlandia, Uberlandia, MG, Brazil
Venue:
ISC '07 Proceedings of the 10th IASTED International Conference on Intelligent Systems and Control
Year:
2007

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Abstract

Genetic algorithms (GAs) are algorithms used in various applications with the intent of increasing optimization, however, the process of improving the solution, is normally, slow and computationally costly, as it involves the use of some genetic operators. Depending on a problem's complexity, its solution may take days, weeks or months to reach. For this reason, in this paper a genetic operator was developed, called Assisted Recombination, which together with the operators of selection, mutation and recombination make up the proposed GA, the realization of this objective will facilitate the genetic improvements. Two groups of experiments were applied and their results, which when compared to the canonic GA, showed that the proposed GA yields a good performance.