The problem of assigning students to course sections in a large engineering school
Computers and Operations Research
Computerised decision aid for timetabling: a case analysis
Discrete Applied Mathematics - Special issue: Timetabling and chromatic scheduling
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Network flows: theory, algorithms, and applications
An algorithm for class scheduling with section preference
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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
Recent Developments in Practical Course Timetabling
PATAT '97 Selected papers from the Second International Conference on Practice and Theory of Automated Timetabling II
A Computational Study of a Cutting Plane Algorithm for University Course Timetabling
Journal of Scheduling
Constraint satisfiability algorithms for interactive student scheduling
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
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
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The students of the Industrial Design department at the TU Eindhoven are allowed to design part of their curriculum by selecting courses from a huge course pool. They do this by handing in ordered preference lists with their favorite courses for the forthcoming time period. Based on this information (and on many other constraints), the department then assigns courses to students. Until recently, the assignment was computed by human schedulers who used a quite straightforward greedy approach. In 2005, however, the number of students increased substantially, and as a consequence the greedy approach no longer yielded acceptable results. This paper discusses the solution of this real-world timetabling problem. We present a complete mathematical formulation of it, and we explain all the constraints resulting from the situation in Eindhoven. We solve the problem using lexicographical optimization with four subproblems. For all four subproblems, an elegant integer linear programming model is given which easily can be put into CPLEX. Finally, we report on our computational experiments and results around the Eindhoven real-world data.