A survey of practical applications of examination timetabling algorithms
Operations Research
Scheduling examinations to reduce second-order conflicts
Computers and Operations Research
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 Genetic Algorithm Solving a Weekly Course-Timetabling Problem
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
Generating Complete University Timetables by Combining Tabu Search with Constraint Logic
PATAT '97 Selected papers from the Second International Conference on Practice and Theory of Automated Timetabling II
Recent Developments in Practical Course Timetabling
PATAT '97 Selected papers from the Second International Conference on Practice and Theory of Automated Timetabling II
Some Observations about GA-Based Exam Timetabling
PATAT '97 Selected papers from the Second International Conference on Practice and Theory of Automated Timetabling II
Improving a Lecture Timetabling System for University-Wide Use
PATAT '97 Selected papers from the Second International Conference on Practice and Theory of Automated Timetabling II
A Comparison of Annealing Techniques for Academic Course Scheduling
PATAT '97 Selected papers from the Second International Conference on Practice and Theory of Automated Timetabling II
Off-the-Peg or Made-to-Measure? Timetabling and Scheduling with SA and TS
PATAT '97 Selected papers from the Second International Conference on Practice and Theory of Automated Timetabling II
A multistage evolutionary algorithm for the timetable problem
IEEE Transactions on Evolutionary Computation
A new neural network based construction heuristic for the examination timetabling problem
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Solving effectively the school timetabling problem using particle swarm optimization
Expert Systems with Applications: An International Journal
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
Hi-index | 0.00 |
The main aim of this paper is to consider university examination timetabling problems as multicriteria decision problems. A new multicriteria approach to solving such problems is presented. A number of criteria will be defined with respect to a number of exam timetabling constraints. The criteria considered in this research concern room capacities, the proximity of the exams for the students, the order and locations of events, etc. Of course, the criteria have different levels of importance in different situations and for different institutions. The approach that we adopt is divided into two phases. The goal of the first phase is to find high-quality timetables with respect to each criterion separately. In the second phase, trade-offs between criteria values are carried out in order to find a compromised solution with respect to all the criteria simultaneously. This approach involves considering an ideal point in the criteria space which optimises all criteria at once. It is, of course, generally the case that a solution that corresponds to such a point does not exist. The heuristic search of the criteria space starts from the timetables obtained in the first phase with the aim of finding a solution that is as close as possible to this ideal point with respect to a certain defined distance measure. The developed methodology is validated, tested and discussed using real world examination data from various universities.