Abstract: The creation and generation of schedules that are free of conflicts manually every academic semester present higher education institutions with a duty that is laborious and demanding of their resources. The course timetabling optimization, as an education timetabling problem, is a popular example of an NP-hard combinatorial problem. Numerous attempts have been made over the course of the past few decades to find a solution to this problem, but no one has yet developed a foolproof approach that can examine all alternatives to find the best method. The promising swarm-based optimization algorithm called Whale Optimization Algorithm was heuristically enhanced in the present study and is called HEWOA. It was designed as a solution to the course timetabling problem discussed in the current study. HEWOA was able to generate an efficient timetable for the large dataset of 1700 events for an average time of 14.92 seconds only, with an average generation of 7.2 and a best time of 8.38 seconds. These results reveal that the performance of HEWOA was better than that of various hybrids of the Genetic Algorithm that was compared in the present study.

Lea D. Austero, Ariel M. Sison, Junrie B. Matias and Ruji P. Medina, “Optimizing Faculty Workloads and Room Utilization using Heuristically Enhanced WOA” International Journal of Advanced Computer Science and Applications(IJACSA), 13(11), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0131164

@article{Austero2022,
title = {Optimizing Faculty Workloads and Room Utilization using Heuristically Enhanced WOA},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131164},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131164},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {11},
author = {Lea D. Austero and Ariel M. Sison and Junrie B. Matias and Ruji P. Medina}
}