The documentation says this:
- 'fitscalingrank' — The default fitness scaling function, 'fitscalingrank', scales the raw scores based on the rank of each individual instead of its score. The rank of an individual is its position in the sorted scores. An individual with rank r has scaled score proportional to 1/√r. So the scaled score of the most fit individual is proportional to 1, the scaled score of the next most fit is proportional to 1/√2, and so on. Rank fitness scaling removes the effect of the spread of the raw scores. The square root makes poorly ranked individuals more nearly equal in score, compared to rank scoring. For more information, see Fitness Scaling.
- 'fitscalingprop' — Proportional scaling makes the scaled value of an individual proportional to its raw fitness score.
In other words, 'fitscalingprop' basically does not scale the score, but 'fitscalingrank' scales the score proportional to its square root. The 'fitscalingrank' explanation expands on the effect of this nonlinear transformation.
Alan Weiss
MATLAB mathematical toolbox documentation
