The Underlying Similarity of Diversity Measures Used in Evolutionary Computation
In this paper we compare and analyze the various diversity measures used in the Evolutionary Computation field. While each measure looks quite different from the others in form, we surprisingly found that the same basic method underlies all of them: the distance between all possible pairs of chromosomes/organisms in the population. This is true even of the Shannon entropy of gene frequencies. We then associate the different varieties of EC diversity measures to different diversity measures used in Biology. Finally we give an O(n) implementation for each of the diversity measures (where n is the population size), despite their basis in an O(n2) number of comparisons.
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