Computer Science – Neural and Evolutionary Computing
Scientific paper
2005-04-11
Proc. Genetic and Evolutionary Computation Conference (GECCO 2005) 1271-1278
Computer Science
Neural and Evolutionary Computing
8 two-column pages, 19 figures
Scientific paper
A commonly experienced problem with population based optimisation methods is the gradual decline in population diversity that tends to occur over time. This can slow a system's progress or even halt it completely if the population converges on a local optimum from which it cannot escape. In this paper we present the Fitness Uniform Deletion Scheme (FUDS), a simple but somewhat unconventional approach to this problem. Under FUDS the deletion operation is modified to only delete those individuals which are "common" in the sense that there exist many other individuals of similar fitness in the population. This makes it impossible for the population to collapse to a collection of highly related individuals with similar fitness. Our experimental results on a range of optimisation problems confirm this, in particular for deceptive optimisation problems the performance is significantly more robust to variation in the selection intensity.
Hutter Marcus
Legg Shane
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