A New Greedy Algorithm for the Curriculum-based Course Timetabling Problem

This study describes a novel greedy algorithm for optimizing the well-known Curriculum-Based Course Timetabling (CB-CTT) problem. Greedy algorithms are good alternative to brute-force and evolutionary algorithms, which take long time execute in order find best solution. Rather than employing single heuristic, as many do, we define apply 120 new heuristics same problem instance. To assign courses available rooms, our proposed employs Largest-First, Smallest-First, Best-Fit, Average-weight first, Highest Unavailable course-first heuristics. Extensive experiments carried out on 21 instances from benchmark set of Second International Competition (ITC-2007). For 18 problems with significantly reduced soft-constraint values, can report zero hard constraint violations (feasible solutions). The outperforms state-of-the-art terms performance.