A large scale timetabling problem
Computers and Operations Research
Partial constraint satisfaction
Artificial Intelligence - Special volume on constraint-based reasoning
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
A filtering algorithm for constraints of difference in CSPs
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Semiring-based constraint satisfaction and optimization
Journal of the ACM (JACM)
Record breaking optimization results using the ruin and recreate principle
Journal of Computational Physics
Backjump-based backtracking for constraint satisfaction problems
Artificial Intelligence
Local search with constraint propagation and conflict-based heuristics
Artificial Intelligence
A Survey of Automated Timetabling
Artificial Intelligence Review
Complete University Modular Timetabling Using Constraint Logic Programming
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
Building University Timetables Using Constraint Logic Programming
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
How to Decompose Constrained Course Scheduling Problems into Easier Assignment Type Subproblems
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
Using Oz for College Timetabling
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
A Comprehensive Course Timetabling and Student Scheduling System at the University of Waterloo
PATAT '00 Selected papers from the Third International Conference on Practice and Theory of Automated Timetabling III
Resource-Constrained Project Scheduling and Timetabling
PATAT '00 Selected papers from the Third International Conference on Practice and Theory of Automated Timetabling III
A Heuristic Incremental Modeling Approach to Course Timetabling
AI '98 Proceedings of the 12th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Constraint Processing
Solving weighted CSP by maintaining arc consistency
Artificial Intelligence
A Computational Study of a Cutting Plane Algorithm for University Course Timetabling
Journal of Scheduling
An effective hybrid algorithm for university course timetabling
Journal of Scheduling
Practice and Theory of Automated Timetabling V: 5th International Conference, PATAT 2004, Pittsburgh, PA, USA, August 18-20, 2004, Revised Selected Papers (Lecture Notes in Computer Science)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
A survey of dynamic scheduling in manufacturing systems
Journal of Scheduling
Journal of Artificial Intelligence Research
Domain filtering consistencies
Journal of Artificial Intelligence Research
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
INFORMS Journal on Computing
Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
A perspective on bridging the gap between theory and practice in university timetabling
PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
Modeling and solution of a complex university course timetabling problem
PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
The teaching space allocation problem with splitting
PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
An open interactive timetabling tool
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
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
Minimal perturbation problem in course timetabling
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
Interactively solving school timetabling problems using extensions of constraint programming
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
Hi-index | 0.00 |
This paper summarizes the work done to solve a complex course timetabling problem at a large university and provides new insights into the overall timetabling process. The first step in the successful solution of this problem was to define a course structure model that allowed application of classical course timetabling methods. Several methods were necessary to solve the complete problem. First, support procedures were needed to detect and correct an infeasible problem where hard constraints were being violated. The resulting timetabling problem was then solved via a search for a complete assignment of times and rooms to classes, taking all hard and soft constraints into account. Methods were also developed for modifying a computed solution in response to changes introduced at a later time while having a minimal impact on existing assignments.These problems are described formally using a weighted constraint satisfaction model of the timetabling problem and solutions are proposed through two types of the algorithms: (1) generic iterative forward search with conflict-based statistics, and (2) branch and bound. Experimental results from the course timetabling system developed for Purdue University are provided. These include solutions computed by university schedulers using the system for two separate terms along with extensive experiments solving two central and six departmental problems, individually, and as a combined problem with almost 2,500 classes. The system described is currently used on all of the many varied course timetabling problems encountered each term at Purdue University.