Exam Timetabling Problem Using Cooperative Hyper-heuristics: A Case Study of the ITC2007 Dataset

In recent years, selection-based hyper-heuristics have shown success across various problem domains, significantly enhancing performance in complex optimization tasks. These hyper-heuristics rely on an effective ensemble of heuristic selection and move acceptance strategies to achieve optimal results. To further advance this field, we propose a novel cooperative hyper-heuristic approach that introduces a three-level agent-based framework, which incorporates multiple cooperative schemes to enhance solution exploration. Our evaluation focuses on exam timetabling problems, where collaboration among agents enables a broader investigation of feasible solutions within the same computational time constraints. Experimental results from the ITC2007 dataset reveal that our approach not only improves hyper-heuristic performance but also maintains robustness compared to existing state-of-the-art methods.