A fuzzy genetic algorithm with local search for university course timetabling

University course timetabling is one of the most important and time-consuming problems in all educational institutions. This problem is in class of NP-hard problem and is very difficult to solve by classic algorithms. Therefore optimization techniques are used to solve them and produce optimal or near optimal feasible solutions instead of exact solutions. Genetic algorithms are considered as an efficient approach for solving this type of problems. This paper presents a fuzzy genetic algorithm (GA) with a local search for solving university course timetabling problem (UCTP). The local search is applied to use its exploitive search ability to improve the search efficiency of the proposed GA. Fuzzy logic is used to measure violation of soft constraints in fitness function to deal with inherent uncertainly and vagueness involved in real life data. The experimental results indicate that the proposed GA is able to produce promising results for the UTCP.