This paper shows an example of how simulated evolution can be applied to a practical optimization problem, and more specifically, how the addition of co-evolving parasites can improve the procedure by preventing the system from sticking at local maxima. Firstly an optimization procedure based on simulated evolution and its implementation on a parallel computer are described. Then an application of this system to the problem of generating minimal sorting networks is described. Finally it is shown how the introduction of a species of co-evolving parasites improves the efficiency and effectiveness of the procedure.
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