Abstract
The goal of this paper is to study if there is a dependency between the probability of crossover with the genetic similarity (in terms of hamming distance) and the fitness difference between two individuals. In order to see the relation between these parameters, we will find a neural network that simulates the behavior of the probability of crossover with these differences as inputs. An evolutionary algorithm will be used, the goodness of every network being determined by a genetic algorithm that optimizes a well-known function.
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Martín, J.L.FV., Sánchez, M.S. (2002). Does Crossover Probability Depend on Fitness and Hamming Differences in Genetic Algorithms?. In: Dorronsoro, J.R. (eds) Artificial Neural Networks — ICANN 2002. ICANN 2002. Lecture Notes in Computer Science, vol 2415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46084-5_63
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DOI: https://doi.org/10.1007/3-540-46084-5_63
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