| Finding optimal solutions for large scale university timetabling problems that satisfy all operational needs and rules in an academic institution, while at the same time fulfill as many of the wishes and requirements of the lecturers and the students as possible, is an important but extremely difficult task for the staff involved. Hence, automating this entire process seems to be inevitable. As timetabling problems are in general NP-complete, several heuristic algorithms have been proposed and applied to solve the problem in the literature. But prior to implementation, it is not clear which would perform better for any specific timetabling problem. This triggers the need for developing an algorithm independent platform that could interface with all solver engines. The main objectives of this work are the following: i) Providing an algorithm-independent tool that can be used to define the resources needed to create and modify an academic schedule, ii) Automatically generate schedules that better fit the needs of both lecturers and students, and iii) Reduce the labor cost involved in the university timetabling problem process. |
