A novel educational timetabling solution through recursive genetic algorithms

This paper addresses the Educational Timetabling Problem for multiple courses. This is a complex problem that basically involves a group of agents such as professors and lectures that must be weekly scheduled. The goal is to find solutions that satisfy the hard constraints and minimize the soft constraint violations. Moreover, universities often differ in terms of constraints and number of professors, courses and resources involved which increases the problem size and complexity. In this work we propose a simple, scalable and parameterized approach to solve Timetabling Problems for multiple courses by applying Genetic Algorithms recursively, which are efficient search methods used to achieve an optimal or near optimal timetable.