Fitness Distance Correlation as a Measure of Problem Difficulty for Genetic Algorithms

@inproceedings{Jones1995FitnessDC,
  title={Fitness Distance Correlation as a Measure of Problem Difficulty for Genetic Algorithms},
  author={Terry Jones and Stephanie Forrest},
  booktitle={ICGA},
  year={1995}
}
A measure of search difficulty, fitness distance correlation (FDC), is introduced and its power as a predictor of genetic algorithm (GA) performance is investigated. The sign and magnitude of this correlation can be used to predict the performance of a GA on many problems where the global maxima are already known. FDC can be used to correctly classify easy deceptive problems and easy and difficult non-deceptive problems as difficult, it can be used to indicate when Gray coding will prove better… CONTINUE READING

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