Fuzzy Genetic Heuristic for University Course Timetable Problem

University Course Timetable Problem is NP-Hard combinatorial optimization problem which lacks analytical solution methods. It has received tremendous attention from disciplines like Operations Research and Artificial Intelligence during past few years given its wide use in universities. Several algorithms have been proposed most of which are based on heuristics like Search techniques and Evolutionary Computation. We present Fuzzy Genetic Heuristic Algorithm to solve the problem. The method incorporates Genetic Algorithms using indirect representation based on event priorities, Micro Genetic Algorithms and heuristic Local Search operators to tackle real world Timetable Problem from St. Xavier's College, India. Fuzzy Set models measure of violation of soft constraint in fitness function to take care of inherent uncertainty and vagueness involved in real life data. The solutions are developed with respect to manual solution developed by College staff. The proposed technique satisfies all hard constraints of problem and achieves significantly better score in satisfying soft constraints. The algorithm is computationally intensive in comparison to standard Genetic Algorithm based benchmark heuristics. The reduction computational complexity of the algorithm can be considered as future work for further research.

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