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Abstract
This paper proposes a new approach based on two explicit rules of Mendel experiments and Mendel's population genetics for the genetic algorithm (GA). These rules are the segregation and independent assortment of alleles, respectively. This new approach has been simulated for the optimization of certain test functions. The doctrinal sense of GA is conceptually improved by this approach using a Mendelian framework. The new approach is different than the conventional one in terms of crossover, recombination, and mutation operators. The results obtained here are in agreement with those of the conventional GA, and even better in some cases. These results suggest that the new approach is overall more sensitive and accurate than the conventional one. Possible ways of improving the approach by including more genetic formulae in the code are also discussed.