The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Genetic Algorithms and Grouping Problems
Genetic Algorithms and Grouping Problems
A Memetic Algorithm for University Exam Timetabling
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
A Grouping Genetic Algorithm for Graph Colouring and Exam Timetabling
PATAT '00 Selected papers from the Third International Conference on Practice and Theory of Automated Timetabling III
A MAX-MIN Ant System for the University Course Timetabling Problem
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
Genetic algorithms and timetabling
Advances in evolutionary computing
Applying evolutionary computation to the school timetabling problem: The Greek case
Computers and Operations Research
On the complexity of time table and multi-commodity flow problems
SFCS '75 Proceedings of the 16th Annual Symposium on Foundations of Computer Science
The effect of neighborhood structures on tabu search algorithm in solving course timetabling problem
Expert Systems with Applications: An International Journal
An informed genetic algorithm for the examination timetabling problem
Applied Soft Computing
INFORMS Journal on Computing
Ant algorithms for the university course timetabling problem with regard to the state-of-the-art
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
A memetic algorithm for course timetabling
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A multistage evolutionary algorithm for the timetable problem
IEEE Transactions on Evolutionary Computation
Finding Feasible Timetables Using Group-Based Operators
IEEE Transactions on Evolutionary Computation
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Timetabling is the problem of scheduling a set of events while satisfying various constraints. In this paper, we develop and study the performance of an evolutionary algorithm, designed to solve a specific variant of the timetabling problem. Our aim here is twofold: to develop a competitive algorithm, but more importantly, to investigate the applicability of evolutionary operators to timetabling. To this end, the introduced algorithm is tested using a benchmark set. Comparison with other algorithms shows that it achieves better results in some, but not all instances, signifying strong and weak points. To further the study, more comprehensive tests are performed in connection with another evolutionary algorithm that uses strictly group-based operators. Our analysis of the empirical results leads us to question single-level selection, proposing, in its place, a multi-level alternative.