Efficiently Solving High School Timetable Scheduling Problems with Various Neighborhood Operators
Lijian Xiao, Xinhui Zhang, Subhashini Ganapathy
Proceedings of the 17th International Multi-Conference on Society, Cybernetics and Informatics: IMSCI 2023, pp. 131-137 (2023); https://doi.org/10.54808/IMSCI2023.01.131
|
The 17th International Multi-Conference on Society, Cybernetics and Informatics: IMSCI 2023
Virtual Conference September 12-15, 2023 Proceedings of IMSCI 2023 ISSN: 2831-722X (Print) ISBN (Volume): 978-1-950492-74-9 (Print) |
|
Abstract
The high school timetable scheduling problem involves assigning lectures to students, faculty, and classrooms while meeting specific constraints. This study focuses on the challenging high school course scheduling problem in China, where subject choices and complex timetable rules make finding feasible and optimal solutions difficult. By successfully addressing this complex course scheduling problem, we hope to contribute to the improvement of education systems around the world. Simulated annealing, a novel algorithm that considers soft constraints and preferences, is proposed to address this problem. The algorithm utilizes different neighborhood operators to tackle various aspects of the problem, resulting in efficient and effective solutions. The research has important implications for similar timetabling problems in the academic and practical domains.
|
||