The development of the aviation industry in Indonesia in the past decade has risen sharply. One of the impacts of the development of the aviation industry was the presence of a multilevel tariff concept. Where, the concept is the variation in ticket prices in one class with slightly different facilities such as the difference in penalty fees for making refunds and rebooking. The concept of multilevel rates is usually referred to as sub-class rates. One application of the sub-class tariffs in economic classes is divided into four types of sub-classes special promo sub-classes, promo sub-classes, then affordable sub-class and flexible sub-class. One optimization method of getting a combination that meets the requirements without having to try all possibilities is the Genetic Algorithm. The chromosomes built represent 10 subclasses on 9 routes so that they have 90 genes. The use of genetic algorithms originated from the generation of an initial population of 8 chromosomes with a length of 90 genes performed randomly, evaluation of the compatibility function was then selected using the Rank based fitness technique, crosses using Multi-Point Crossover, mutations with the Mutation Insertion technique. The system built was tested with two conditions each of eight tests with 100 generations. First, the test uses the mutation method of three subclass codes on four routes at a capacity of 150 seats, obtained the largest match value of Rp. 750,752,200 and the smallest Rp. 662,283,100. And testing with the mutation method of three subclass codes on eight routes of 150 seat capacity obtained the largest match value of Rp. 763,265,300 and the smallest Rp. 547,396,200. The results of testing the mutation method on eight routes resulted in a higher match value compared to the mutation method on four routes. The system has been implemented in software so that it can provide recommendations on the number of ticket passes distributed in the economic subclass.