Abstract
The article presents an analysis of seven crossover operators for continuous spaces applied for Diploid Genetic algorithms (DGA). Unlike the classical ones, called in genetic “haploid” in which an individual is synonym with a chromosome, the individuals of DGA carry two chromosomes, which brings in intrinsic diversity in the population. The impact of the recombination operators is analyzed and compared, turning out that BLX operators yields the best results and uniform and arithmetic crossover the worst. With respect to specificity, the uniform crossover and two point crossover have the lowest standard deviation of the results .
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Petrovan, A., Matei, O., Erdei, R. (2021). A Behavioural Study of the Crossover Operator in Diploid Genetic Algorithms. In: Herrero, Á., Cambra, C., Urda, D., Sedano, J., Quintián, H., Corchado, E. (eds) 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020). SOCO 2020. Advances in Intelligent Systems and Computing, vol 1268. Springer, Cham. https://doi.org/10.1007/978-3-030-57802-2_8
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