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The size of the population can be critical in many applications of genetic algorithms. If the population size is too small, the genetic algorithm may converge too quickly; if it is too large, the genetic algorithm may waste computational resources; the waiting time for an improvement might be too long. We propose an adaptive method for maintaining variable population size, which grows and shrinks together according to some characteristic of the search. The first experimental results indicate some merits of the proposed method.>
Arabas et al. (Tue,) studied this question.
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