Solving Class Timetabling Problem of IIT Kanpur using Multi-Objective Evolutionary Algorithm

Unlike in many other universities, preparation of class timetable in IIT Kanpur is very laborious and complicated. It contains different types of classes, among which most of the common classes are either split or grouped. Many split classes are divided up to five parts, while many sets of group classes contain up to twenty classes. The entire timetable is composed of two phases. The first phase contains all the common compulsory classes of the institute, which are scheduled by a central team. The second phase contains the individual departmental classes. Presently this timetable is prepared manually, by manipulating those of earlier years, with the only aim of producing a feasible timetable. The potentiality of evolutionary algorithms (EAs) have been exploited in the present work to schedule the classes of the first phase of the problem. Using NSGA-II-UCTO, a multi-objective EA-based university class timetable optimizer, a number of trade-off solutions, in terms of multiple objectives of the problem, could be obtained very easily. Moreover, each of the obtained solutions has been found much better than a manually prepared solution which is in use.