<![CDATA[The Train passengers do not increase over time continuously. Each route provided by PT.KAI does not always meet the capacity of the total seats in each class. On some predetermined route, there are seats which are not optimally filled in each class, it can increase the operational costs because of the unused wagon stay to run even though there are no passengers. Optimization is one way to find the best value of a giveing the function in an available context. One of the methods used for optimization is Genetic Algorithm. Genetic Algorithm is a method to get a solution according to the criteria without the need to test all combinations. The stages of the genetic algorithm consist of four stages, there are input, pre-process, process and output. The Genetic Algorithm process includes initial solution generation, match value evaluation, selection, mutation and crosses. This system is tested by entering the number of passengers 250, 500, and 750 people. The number of 250 passengers with 100 generations produces an optimal fitness value, namely 241 seats in the 82nd generation with a percentage of 98.18%. The purpose of this research is to optimize the use of class wagon on passenger trains according to the schedule of each train.]]>
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