  We model the problem of optimizing the schedule of courses a student at the
American College of Greece will need to take to complete their studies. We
model all constraints set forth by the institution and the department, so that
we guarantee the validity of all produced schedules. We formulate several
different objectives to optimize in the resulting schedule, including fastest
completion time, course difficulty balance, and so on, with a very important
objective our model is capable of capturing being the maximization of the
expected student GPA given their performance on passed courses using Machine
Learning and Data Mining techniques. All resulting problems are Mixed Integer
Linear Programming problems with a number of binary variables that is in the
order of the maximum number of terms times the number of courses available for
the student to take. The resulting Mathematical Programming problem is always
solvable by the GUROBI solver in less than 10 seconds on a modern commercial
off-the-self PC, whereas the manual process that was installed before used to
take department heads that are designated as student advisors more than one
hour of their time for every student and was resulting in sub-optimal schedules
as measured by the objectives set forth.
