This paper refers to the implementation of a computer program which employs Genetic Algorithm in the quest for an optimal class schedule generator. Genetic Algorithm theory is covered with emphasis on less fully encoded systems employing non-genetic operators. The field of automated class scheduling system of UIC-ITE is also explored. The program, written in Visual Basic Language, incorporates a repair strategy for faster evolution. The effects and representation of altered mutation rate and population size are tested. It is seen that the Genetic Algorithm could be improved by further incorporating repair strategies, and is readily scalable to address scheduling problem. Using the genetic algorithm principles, an alternative class scheduling system was developed which consequently resulted to good schedules and efficient use of each classroom in relation to time, space and constraints. The Genetic Algorithm program initializes a single schedule randomly representing a single individual.