Abstract
It is proposed that the comparison problem of two models of the genetic algorithm, the steady state genetic algorithm and the elitist selection genetic algorithm. The convergence speed, on-line and off-line performance of the hvo algorithms in different environments are compared. It is experimentally shown that the steady state genetic algorithm is a simple, effective genetic algorithm. The steady state genetic algorithm runs well in low-dimensional environment, especially its good on-line performance. On the other hand the elitist selection genetic algorithm runs well in highdimensional environment, it has good capability in searching optimal value in a big space. The diffmnce between the searching ability of two algorithms was explained by the theory of Implicit Parallelism. The difference between the two algorithms on-line performances was explained by the difference ways of reproduction the two models used.
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