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Selection in the Presence of Noise
Jürgen Branke and Christian Schmidt
Institute AIFB,
University of Karlsruhe,
76128 Karlsruhe, Germany
{branke,csc}@aifb.uni-karlsruhe.de
Abstract.
For noisy optimization problems, there is generally a trade-off between
the effort spent to reduce the noise (in order to allow the
optimization algorithm to run properly), and the number of solutions
evaluated during optimization. However, for stochastic search algorithms like evolutionary
optimization, noise is not always a bad thing. On the contrary,
in many cases, noise has a very similar effect to the
randomness which is purposefully and deliberately introduced
e.g. during selection.
Using the example of stochastic tournament selection, we show that
the noise inherent in the optimization problem should be taken into
account by the selection operator, and that one should not reduce
noise further than necessary.
Keywords: Noise, tournament selection, stochastic fitness
LNCS 2723, p. 766 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003