Timetabling Problems have been widely studied, given its practical and theorical relevance. Most of its variations belong to the NP-Hard class of problems. In general, it is about allocation of material and human resources in time and space, aiming to optimize some set of defined objetives. In University Course Timetabling, for example, the objective might be the satisfaction of professors and the academic performance of students. In the last years, the formulations for timetabling problems proposed by the In- ternational Timetabling Competition (ITC) have been widely adopted. The predominance of meta-heuristics and local search-based methods is remark- able among the recently proposed approaches. The objetive of this thesis is to propose algorithms for the Post Enrolment-based Course Timetabling Problem of the ITC, focusing on Mathematical Programming-based heuris- tic methods. Among the Mixed Integer Linear Programming models that we propose for this problem, we highlight the one based on the Asymetric Representatives Formulation for the Graph Coloring Problem. We explore the application of the Local Branching heuristic and we propose a Column Generation solution procedure, as an attempt to handle the proposed models, given that the complexity of such models poses a challenge for currently available Mixed Integer Linear Programming solvers.