Fitness Uniform Deletion: A Simple Way to Preserve Diversity

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dc.creatorLegg, Shane
dc.creatorHutter, Marcus
dc.date2005-04-11
dc.date.accessioned2026-07-07T06:33:27Z
dc.date.available2026-07-07T06:33:27Z
dc.descriptionA 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.
dc.description8 two-column pages, 19 figures
dc.identifierhttps://arxiv.org/abs/cs/0504035
dc.identifierhttp://arxiv.org/abs/cs/0504035
dc.identifierProc. Genetic and Evolutionary Computation Conference (GECCO 2005) 1271-1278
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/99200
dc.subjectNeural and Evolutionary Computing
dc.subjectArtificial Intelligence
dc.subjectI.2.M
dc.titleFitness Uniform Deletion: A Simple Way to Preserve Diversity
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