| dc.description.abstract | In schools all over the world, weeks are spent each year trying to schedule timetables. These timetables usually follow specific rules, and have some restrictions they need to fulfill. By using an automated method for timetable generation that take these rules and restriction into consideration, one could relieve school employees hours of administrative work. The timetable problem is well known, and has been subject to a number of studies over the past decades. Proposed solutions to this task uses a wide range of methods, from binary integer programming to heuristics like simulated annealing\cite{simAnn}. Some companies also sell timetable software or services, yet none seems to offer any module or component that might be integrated into other systems.
In this thesis, such a module has been created based on binary integer programming with Gurobi as optimizer. The module is made with secondary schools in mind, yet is flexible in the sense that it is easy to modify the restrictions a timetable has to follow. The system can either solve a more traditional timetable problem for a data set where teachers are pre assigned to their lessons, or solve a resource management part that decides which lectures a teacher should be assigned to. While the system has only been tested on a limited number of data sets, the results are quite promising. However, while the timetable part is solved optimally for all cases, the final specifications and data set for resource management came in to late for proper testing, and to late to finalize that model part. While this thesis has come a long way, it lacks a proper application programming interface (API) to ease the integration into other applications. Also, while the system is made according to some specifications, one should test and discuss the module more with schools before it can be used by industry. | en |
