An Experimental Study of the Genetic Algorithm Convergence
Abstract
Genetic algorithm is a well-known heuristic search algorithm, typically used to generate valuable solutions to optimization and search problems. The most important operation in a genetic algorithm is crossover, as it has the greatest effect on its convergence rate. Therefore, in order to achieve the most optimal results in a reasonable time, one has to decide on the crossover type, as well as make a selection of a crossover point. In order to explore the effect of the crossover point selection methods on the convergence rate, we conducted experiments based on different crossover point selection criteria, whereby the results indicate the high importance of controlling the randomization of the crossover point selection range.Downloads
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