GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
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This article investigates various local operators in a discrete (1, λ)-setting applied to tracking problems, a specific class of non-stationary problems. In the first instance, the influence of operator properties on the tracking performance is examined. Both the enforcement of bigger steps and, especially, directed mutations are found to increase the tracking accuracy considerably. For the examination of highly time restricted problems, a correlation between the population size and the severity of the problem dynamics is assumed. Relatively large population sizes are found to be advantageous if the number of evaluations has a big influence on the severity. All results are obtained using a fixpoint analysis of a worst-case model as well as simulations within a two-dimensional Markov model.