Fuzzy Genetic Heuristic for University Course Timetable Problem

University Course Timetable Problem is NP-Hard combinatorialoptimization problem which lacks analytical solution methods. It hasreceived tremendous attention from disciplines like Operations Researchand Artificial Intelligence during past few years given its wide use inuniversities. Several algorithms have been proposed most of which arebased on heuristics like Search techniques and Evolutionary Computation. We present Fuzzy Genetic Heuristic Algorithm to solve the problem. Themethod incorporates Genetic Algorithms using indirect representationbased on event priorities, Micro Genetic Algorithms and heuristic LocalSearch operators to tackle real world Timetable Problem from St. Xavier’sCollege, India. Fuzzy Set models measure of violation of soft constraint infitness function to take care of inherent uncertainty and vagueness involvedin real life data. The solutions are developed with respect to manualsolution developed by College staff. The proposed technique satisfies allhard constraints of problem and achieves significantly better score insatisfying soft constraints. The algorithm is computationally intensive incomparison to standard Genetic Algorithm based benchmark heuristics. The reduction computational complexity of the algorithm can be consideredas future work for further research