The study presents the possibility of inducing genetic adaptations within one generation using a hybrid algorithm that combines genetic and particle swarm algorithms. By modeling a population of ten individuals, the rapid evolution of the lactase gene (LCT) associated with lactose digestion is simulated. The innovative hybrid model takes advantage of genetic and swarm algorithms to efficiently simulate genetic mutations and natural selection processes, potentially accelerating the emergence of beneficial genetic adaptations that typically take several generations to manifest. This approach not only highlights the basic aspects of genetic engineering, but also expands the possibilities for future genetic research in the field of human adaptation and health. The results show considerable potential for finding similar solutions for lactase in a simulated population, opening up a new perspective on how genetic engineering can accelerate evolutionary processes in humans.