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Finite and infinite population models of the canonical genetic
algorithm are presented, as well as extentions to include local
search and permutation-based representations. We illustrate
that the p-vector representing the infinite population trajectory
also represented the sampling distribution used by the finite
population model. The schema theorem and the concept of implicit
parallelism are reviewed. The relationship between these models
and other forms of evolutionary algorithms will also be explored,
as well as their potential for better understanding parallel
evolutionary algorithms.
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