Memetic techniques for examination timetabling

In this paper, we investigate the effectiveness of combining the main components of the memetic algorithms (MAs) on the quality of solutions produced for Uncapacitated Examination Timetabling Problem (UETP). These components are recombination, randomness, and neighbourhood structures. The Harmony Search Algorithm (HSA), which is a variation of MA, is used to perform different combinations of these components. It has three main components: Memory Consideration using the recombination, Random Consideration using the randomness and Pitch Adjustment using the neighbourhood structures (or local search). The combinations among MA components are evaluated using 17 different scenarios each of which reflects a combination of one, two or three components. The results show that the system that combines the three components (recombination, randomness, and neighbourhood structures) provides the best results. Furthermore, the best results obtained from the convergence scenarios were compared with 22 other methods that used a de facto dataset defined by Carter et al. (in Journal of the Operational Research Society 74:373-383, 1996) for UETP. The results exceed those produced by the previous methods in 2 out of 12 datasets.