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The Underlying Similarity of Diversity Measures Used in Evolutionary Computation
Mark Wineberg1 and Franz Oppacher2
1Computing and Information Science
University of Guelph
Guelph, Canada
wineberg@cis.uoguelph.ca
2School of Computer Science
Carleton University
Ottawa, Canada
oppacher@scs.carleton.ca.ca
Abstract.
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 
implementation for each of the diversity measures (where n is the
population size), despite their basis in an 
number of
comparisons.
LNCS 2724, p. 1493 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003