Abstract—Genetic Algorithms (GA), developed several decades ago, are widely used to solve optimization problems. Since the invention of genetic algorithms, significant progress has been made in genetics, leading to the discovery of many new mechanisms of heredity that were not previously incorporated into genetic algorithms. One such group is epigenetic processes. The article presents two epigenetic-based operations used in genetic algorithms: cytosine methylation and allele inactivation (gene silencing). This article presents two original versions of genetic algorithms that use epigenetic processes. It presents the results of research on the impact of the introduced modifications on the genetic algorithm's performance. The study examined two optimization problems: the loading optimization problem and the outlier detection problem. The experiments examined the optimal probability of occurrence of the introduced modifications, the average number of iterations of the genetic algorithm with and without modifications required to obtain the optimal result, and compared execution times. The research confirmed that introducing new operations into genetic algorithms can improve their performance.
 
Keywords—Genetic Algorithms (GA), epigenetic process, optimization


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