The Incorporation of Late Acceptance Hill Climbing Strategy in the Deterministic Optimization of Examination Scheduling Framework: A Comparison with the Traditional Hill Climbing

In this study, we are incorporating the Late Acceptance Hill Climbing (LAHC) strategy in the proposed Domain Transformation Approach (DTA) to solve the university examination scheduling problem. This is with the aim to test whether LAHC can substitute the original traditional greedy Hill Climbing (HC) in the proposed framework, in order to clarify that the DTA is flexible enough to accommodate different search procedures in its optimization stage. We would also like to investigate the performance of LAHC in comparison to the HC optimization in producing solutions based on the Toronto standard benchmark datasets problem. Based on our findings, it was shown that LAHC has been incorporated successfully in the proposed DTA and therefore DTA is proven to be very flexible and systematic approach. The LAHC procedure had produced very encouraging results during the experiments. LAHC managed to outperformed HC results for some datasets but on average both quality solutions were on par. Since it is hard to predict the quality of the solutions using LAHC, it is suggested that HC optimization is more reliable, robust and efficient in generating good quality timetables in the proposed DTA framework.