The work utilizes evolution computation techniques to induce association rules based on example data stored in big datasets. The main focus is especially on genetic algorithms, which represent a generic population-based metaheuristic optimization algorithm that uses solution space search mechanisms inspired by biologic evolution, such as recombination, mutation and evolutionary selection. The goal is to describe the process of designing and implementation of own genetic algorithm that will mine the association rules. This includes the definition of solution representation, their evaluation...