Each semester, PUC-Rio students must choose the set of disciplines they will study during the period. This is a process that, ideally, should involve planning prior to the enrollment date, in which students should consider factors such as: the subjects still to be taken, the subjects offered in the period and the schedules of each class available. However, a student s choices in a period can affect all of his/her subsequent periods and, consequently, his/her course conclusion time. In this way, a curriculum grid optimizer was created, which suggests a configuration of the student s curriculum until the end of his graduation. As a case study for this project, curriculum 1, from 2018, of the Control and Automation Engineering course at PUC-Rio was used. This solution considers factors such as how much a subject is a prerequisite for others, the period in which the department suggests that it be studied, and the schedule of the classes available in the current period. The optimizer was built based on integer linear programming, which allows the clear definition of the restrictions imposed for the construction of the curriculum, in addition to allowing the use of efficient algorithms to solve the problem. When comparing the results obtained with the periodization proposed by the University and with grids built manually, it was observed that the optimizer is able to suggest grids similar to these, but with some degrees of customization. In addition, it was also evidenced that the solution developed here can be more customizable, making it increasingly capable of suggesting curriculum grids that consider the individual desires and needs of each student.