Finding a feasible course schedule using Tabu search
Discrete Applied Mathematics - Special issue: Timetabling and chromatic scheduling
Case-based heuristic selection for timetabling problems
Journal of Scheduling
An effective hybrid algorithm for university course timetabling
Journal of Scheduling
Applying evolutionary computation to the school timetabling problem: The Greek case
Computers and Operations Research
New integer linear programming approaches for course timetabling
Computers and Operations Research
A new architecture selection method based on tabu search for artificial neural networks
Expert Systems with Applications: An International Journal
A memetic algorithm for course timetabling
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Solving effectively the school timetabling problem using particle swarm optimization
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Solution approaches to the course timetabling problem
Artificial Intelligence Review
Course timetabling using evolutionary operators
Applied Soft Computing
Hi-index | 12.06 |
The course timetabling problem must be solved by the departments of Universities at the beginning of every semester. It is a though problem which requires department to use humans and computers in order to find a proper course timetable. One of the most mentioned difficult nature of the problem is context dependent which changes even from departments to departments. Different heuristic approaches have been proposed in order to solve this kind of problem in the literature. One of the efficient solution methods for this problem is tabu search. Different neighborhood structures based on different types of move have been defined in studies using tabu search. In this paper, the effects of moves called simple and swap on the operation of tabu search are examined based on defined neighborhood structures. Also, two new neighborhood structures are proposed by using the moves called simple and swap. The fall semester of course timetabling problem of the Department of Statistics at Hacettepe University is solved utilizing four neighborhood structures and the comparison of the results obtained from these structures is given.