Guided Crossover : A New Operator for Genetic Algorithm Based Optimization

@inproceedings{Rasheed1997GuidedC,
  title={Guided Crossover : A New Operator for Genetic Algorithm Based Optimization},
  author={Khaled Rasheed},
  year={1997}
}
Genetic algorithms (GAs) have been extensively used in different domains as a means of doing global optimization in a simple yet reliable manner. They have a much better chance of getting to global optima than gradient-based methods which usually converge to local sub-optima. However, GAs have a tendency of getting only moderately close to the optima in a small number of iterations. To get very close to the optima, the GA needs a very large number of iterations, whereas gradient-based… CONTINUE READING
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