
doi: 10.1007/bfb0029728
This paper presents a new Genetic Algorithm (GA), called Alternative Genetic Algorithm (AGA) which has been defined to facilitate theoretical investigations. We have shown that both AGA and the usual GA (UGA) obey similar difference equations. However, theoretical investigations on the AGA are much simpler than on the UGA. For the AGA, we can derive as a theoretical result the mean function value ‹f› in the population of individuals as a function of time. In an application of this result we show that the experimentally obtained ‹f›A of the AGA approximates the ‹f›U of the UGA within ≈ 1% when fitting the parameter representing the convergence speed, i.e., the mean increase of the mean function value in the population.
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