Hybrid Whale Optimization Algorithm for Solving Timetabling Problems of ITC 2019

Abstract

Timetabling problem at universities is one of the problems that require more attention in operations research. This problem is known as NP-Hard problem, therefore non-deterministic exact algorithm could solve problems within this category within polynomial time. The heuristic approach can produce a fairly good solution within polynomial time but does not guarantee that the solution is optimal. So, there is always a gap in a heuristic algorithm that can be studied to result enhanced algorithm with better performance. There are a lot of timetabling problem domains in the literature that have been well studied in the scientific literature especially in the field of operational research and artificial intelligence. However, there are still few prior studies reported in the literature that focus on solving relatively new timetabling problem domain of International Timetabling Competition 2019 (ITC 2019). The competition presents real-world datasets with high complexity and large problem sizes. This paper reports our study of developing a novel algorithm called the Hybrid Whale Optimization Algorithm to solve the ITC 2019 problem. The algorithm combines the adapted whale optimization algorithm (WOA) and Late Acceptance Hill Climbing (LAHC) algorithm. The experimental results show that The WOA algorithm successfully improved the average penalty value by 65%. Furthermore, the hybrid WOA improves the WOA algorithm even better, especially on four datasets by 16-43%. Compared to other algorithms reported in the competition, the Hybrid WOA algorithm is ranked 7 out of 13.