Fitness Distance Correlation , as statisticalmeasure of Genetic
نویسندگان
چکیده
This paper revisits past works on tness distance correlation (FDC) in relation to genetic algorithms (GA) performance , and puts forth evidence that this statistical measure is relevant to predict the performance of a GA. We propose an interpretation of Hamming-distance based FDC, which takes into account the GA dynamics and the eeects of crossover operator. We base this proposition on the notion of predicates developed by M. D. Vose. The aim of this article is double since, using results obtained with the FDC, it connrms Vose's theory, and starting from this theory, it corroborates FDC as a relevant predictor measure of problem diiculty for GAs.
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