University Course Scheduling Using Evolutionary Algorithms

This paper presents a new heuristic based on evolutionary algorithms and applied to the university course scheduling problem, where a feasible and comfort time tables are required. Here, the idea is to use an evolution program which is a stochastic optimization strategy similar to genetic algorithms. The main difference is that evolutionary programming insists on the behavioral linkage between parents and their offspring rather than seeking to emulate specific genetic operators as observed in nature. The paper starts by defining the problem and determining the constraints under which the solution should be found. Then, the problem model is described with a set of courses, rooms, instructors, and student groups. Finally, the proposed methodology is applied on a real data set from one of the four colleges of our university. Results show that our methodology permits more robust exploration for the search space of the designated problem which gives more optimized time schedules than those performed manually. The obtained results also show that the proposed solutions can solve many registration difficulties.