Abstract
This paper develops a university timetabling decision support system that considers both hard and soft constraints of the problem. A timetable solution must satisfy all hard constraints, and may be only capable of partially meeting soft constraints. We modeled the problem as a Constraint Satisfactory Problem and adapted lexicographic optimization approach to implement the solution procedure; where each soft constraint is treated as an objective with a priority. The solution approach utilizes the solution space reduction nature of constraint propagation to optimize objectives sequentially. Different value assignment strategies for constraint propagation are investigated to explore their robustness and effectiveness in performances. The system allows department management to indicate different combinations of preferences and parameters, and view the resulting timetable and related statistics in real time mode. The resulting timetabling contributes to a better teaching environment for both faculty and students.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Barták, R.: Modeling soft constraints: A Survey. Neural Network World 12(5), 421–431 (2002)
Bessiere, C.: Arc-consistency and arc-consistency again. Artificial Intelligence 65, 179–190 (1994)
Brailford, S.C., Potts, C.N., Smith, B.M.: Constraint satisfaction problems algorithm and applications. European Journal of Operational Research 119, 557–581 (1999)
Burke, E., Erben, W. (eds.): PATAT 2000. LNCS, vol. 2079. Springer, Heidelberg (2001)
Carter, M.W., Laporte, G.: Recent Developments in Practical Examination Timetabling. Interface 4, 3–21 (1996)
Carter, M.W., Laporte, G.: Recent Developments in Practical Course Timetabling. Interface 5, 3–19 (1998)
Cooper, T.B., Kingston, J.H.: The Complexity of Timetabling Construction Problem. Interfaces 17, 183–195 (1996)
Deris, S., Omatu, S., Ohta, H.: Timetable planning using the constraint-based reasoning. Computers & Operations Research 27, 819–840 (2000)
Fahrion, R., Dollansky, G.: Construction of University Faculty Timetables Using Logic Programming. Discrete Applied Mathematics 35(3), 221–236 (1992)
ILOG Inc. ILOG [Computer software]: Mountain View, California (2002)
Schaerf, A.: A Survey of Automated Timetabling. Artificial Intelligence Review 13, 87–127 (1995)
Werra, D.E.: An introduction to timetabling. European Journal of Operational Research 19, 151–162 (1985)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Shue, LY., Lin, PC., Tsai, CY. (2009). Constraint Programming Approach for a University Timetabling Decision Support System with Hard and Soft Constraints. In: Chien, BC., Hong, TP. (eds) Opportunities and Challenges for Next-Generation Applied Intelligence. Studies in Computational Intelligence, vol 214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92814-0_15
Download citation
DOI: https://doi.org/10.1007/978-3-540-92814-0_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-92813-3
Online ISBN: 978-3-540-92814-0
eBook Packages: EngineeringEngineering (R0)