Examination timetabling by computer
Computers and Operations Research
A tabu search heuristic for the vehicle routing problem
Management Science
Coloration neighborhood structures for general graph coloring
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
Tabu Search
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A Survey of Automated Timetabling
Artificial Intelligence Review
Recent Developments in Practical Examination Timetabling
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
A Memetic Algorithm for University Exam Timetabling
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
A multistage evolutionary algorithm for the timetable problem
IEEE Transactions on Evolutionary Computation
A MAX-MIN Ant System for the University Course Timetabling Problem
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
New Algorithms for Examination Timetabling
WAE '00 Proceedings of the 4th International Workshop on Algorithm Engineering
Roulette Wheel Graph Colouring for Solving Examination Timetabling Problems
COCOA '09 Proceedings of the 3rd International Conference on Combinatorial Optimization and Applications
Scatter search technique for exam timetabling
Applied Intelligence
An investigation of the course-section assignment problem
ISCIS'05 Proceedings of the 20th international conference on Computer and Information Sciences
Solving effectively the school timetabling problem using particle swarm optimization
Expert Systems with Applications: An International Journal
The Interleaved Constructive Memetic Algorithm and its application to timetabling
Computers and Operations Research
Some experiments with ant colony algorithms for the exam timetabling problem
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Information Sciences: an International Journal
A hybrid fish swarm optimisation algorithm for solving examination timetabling problems
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
The university course timetabling problem with a three-phase approach
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
A novel similarity measure for heuristic selection in examination timetabling
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
A hybrid multi-objective evolutionary algorithm for the uncapacitated exam proximity problem
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
Examination timetabling with fuzzy constraints
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
Fuzzy multiple heuristic orderings for examination timetabling
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
A hybrid particle swarm optimization based algorithm for high school timetabling problems
Applied Soft Computing
The classroom assignment problem: Complexity, size reduction and heuristics
Applied Soft Computing
Evolutionary algorithms using cluster patterns for timetabling
Intelligent Decision Technologies
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The EXAMINATION TIMETABLING problem regards the scheduling for the exams of a set of universitycourses, avoiding the overlapping of exams having students in common, fairlyspreading the exams for the students, and satisfying room capacity constraints. We present a familyof solution algorithms for a set of variants of the EXAMINATION TIMETABLING problem. The algorithms are based on tabu search, and theyimp ort several features from the research on the GRAPH COLOURING problem. Our algorithms are tested on both public benchmarks and random instances, and theyare compared with previous results in the literature. The comparison shows that the presented algorithms performs as well as constructive methods and memetic algorithms, and onlya decomposition based approach outperforms them in most cases.