Lecture timetabling using hybrid genetic algorithms

The computationally NP-hard timetabling problem has been solved manually for a long time. The problem's complexity has thwarted attempts to use computer based deterministic methods [1, 2, 3], to solve it. More successful approaches have used Genetic Algorithms [5, 6, 11], because they are robust enough in such a huge problem space. In this paper we present new and efficient string encoding schemes and techniques like Optimizer, which improve the performance of the search tremendously. Also presented are results showing the efficient application of these schemes towards the construction of the timetable for a college.