Zhu, K.; Li, L.D.; Li, M. School Timetabling Optimisation Using Artificial Bee Colony Algorithm Based on a Virtual Searching Space Method. Mathematics2022, 10, 73.
Zhu, K.; Li, L.D.; Li, M. School Timetabling Optimisation Using Artificial Bee Colony Algorithm Based on a Virtual Searching Space Method. Mathematics 2022, 10, 73.
Zhu, K.; Li, L.D.; Li, M. School Timetabling Optimisation Using Artificial Bee Colony Algorithm Based on a Virtual Searching Space Method. Mathematics2022, 10, 73.
Zhu, K.; Li, L.D.; Li, M. School Timetabling Optimisation Using Artificial Bee Colony Algorithm Based on a Virtual Searching Space Method. Mathematics 2022, 10, 73.
Abstract
Although educational timetabling problems have been studied for decades, one type, the STP, has not developed as quickly as the other two types due to its diversity and complexity. Also, most of the STP research has only focused on the educators’ availabilities when studying the educator aspect, and the educators’ preferences and expertise have not been taken into consideration. This paper proposes a conceptual model for the school timetabling problem considering educators’ availabilities, preferences and expertise as a whole, and chooses a common real-world school timetabling scenario to study. A mathematical model is presented. A Virtual search space for dealing with the large search space is introduced, and the artificial bee colony algorithm is adapted and applied to the proposed model. The proposed approach is simulated with a random-generated large dataset. The experimental results demonstrate that the proposed approach is able to solve the STP and handle a large dataset in an ordinary computer hardware environment, which significantly reduces computational costs. Compared to the traditional CP method, the proposed approach is more effective and can provide more satisfactory solutions in considering educators’ availabilities, preferences, and expertise levels.
Computer Science and Mathematics, Data Structures, Algorithms and Complexity
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
