Abstract
This paper deals with curriculum-based course timetabling. In particular, we describe the results of a real application at the University of Rome “Tor Vergata.” In this regard, we developed a multi-objective mixed-integer model which attempts to optimize (i) the flow produced by the students enrolled in the lectures, (ii) soft conflicts produced by the possible overlap among compulsory and non-compulsory courses, and (iii) the number of lecture hours per curriculum within the weekdays. The model has been implemented and solved by means of a commercial solver and experiments show that the model is able to provide satisfactory solutions as compared with the real scenario under consideration.
Similar content being viewed by others
References
Al-Yakoob SM, Sherali HD (2007) A mixed-integer programming approach to a class timetabling problem: a case study with gender policies and traffic considerations. Eur J Oper Res 180(3):1028–1044
Badri MA (1996) A two-stage multi-objective scheduling model for faculty-course time assignments. Eur J Oper Res 94:16–28
Bellio R, Ceschia S, Di Gaspero L, Schaerf A, Urli T (2013) A simulated annealing approach to the curriculum-based course timetabling problem. In: Proceedings of the 6th multidisciplinary international conference on scheduling: theory and applications, MISTA 2013, Belgium, pp 314–317
Bellio R, Ceschia S, Di Gaspero L, Schaerf A, Urli T (2014) Feature-based tuning of simulated annealing applied to the curriculum-based course timetabling problem. arXiv:1409.7186
Bettinelli A, Cacchiani V, Roberti R, Toth P (2015) An overview of curriculum-based course timetabling. TOP 23:313–349
Birbas T, Daskalaki S, Housos E (1997) Timetabling for Greek high schools. J Oper Res Soc 48:1191–1200
Bonutti A, De Cesco F, Di Gaspero L, Schaerf A (2012) Benchmarking curriculum-based course timetabling: formulations, data formats, instances, validation, visualization, and results. Ann Oper Res 194(1):59–70
Cacchiani V, Caprara A, Roberti R, Toth P (2013) A new lower bound for curriculum-based course timetabling. Comput Oper Res 40(10):2466–2477
Cambazard H, Demazeau F, Jussien N, David P (2005) Interactively solving school timetabling problems using extensions of constraint programming. In: Burke E, Trick M (eds) LNCS, vol 3616, pp 190–207
Carter MW (2001) A comprehensive course timetabling and student scheduling system at the University of Waterloo. In: Burke E, Erben W (eds) LNCS, vol 2079. Springer, Berlin, pp 64–82
Costa D (1994) A tabu search algorithm for computing an operational timetable. Eur J Oper Res 76:98–110
Colorni A, Dorigo M, Maniezzo V (1992) A genetic algorithm to solve the timetable problem, Technical Report 90-060 revised, Politecnico di Milano Italy
de Werra D (1985) An introduction to timetabling. Eur J Oper Res 19:151–162
Di Gaspero L, McCollum B, Schaerf A (2007) The second international timetabling competition (ITC-2007): curriculum-based course timetabling (track 3). Technical report, School of Electronics, Electrical Engineering and Computer Science, Queens University, Belfast (UK), (site: http://www.cs.qub.ac.uk/itc2007/)
Dimopoulou M, Miliotis P (2001) Implementation of a university course and examination timetabling system. Eur J Oper Res 130:202–213
Geiger MJ (2009) Multi-criteria curriculum-based course timetabling—a comparison of a weighted sum and a reference point based approach. In: Ehrgott M, Fonseca CM, Gandibleux X, Hao JK, Sevaux M (eds) Proceedings of the 5th International Conference on Evolutionary Multi-criterion Optimization, EMO 2009, LNCS, vol 5467. Springer, pp 290–304
Geiger MJ (2012) Applying the threshold accepting metaheuristic to curriculum based course timetabling. Ann Oper Res 194(1):189–202
Gunawan A, Ng KM, Poh KL (2006) A mathematical programming model for a timetabling problem. In: Proceedings of the International Conference on Scientific Computing, Navade, USA
Hao JK, Benlic U (2011) Lower bounds for the ITC-2007 curriculum-based course timetabling problem. Eur J Oper Res 212(3):464–472
Hinkin R, Thompson MG (2002) Schedulexpert: scheduling courses in the Cornell University School of Hotel Administration. Interfaces 32(6):45–57
Junginger W (1986) Timetabling in Germany: a survey. Interfaces 16:66–74
Kiefer A, Hartl R, Schnell A (2014) Adaptive large neighborhood search for the curriculum-based course timetabling problem. Technical report UNIVIE-PLIS-2014-001 University of Vienna
Lach G, Lübbecke M (2012) Curriculum based course timetabling: new solutions to Udine benchmark instances. Ann Oper Res 194(1):255–272
Lü Z, Hao JK, Glover F (2011) Neighborhood analysis: a case study on curriculum-based course timetabling. J Heuristics 17(2):97–118
Lübbecke M (2015) Comments on: an overview of curriculum-based course timetabling. TOP 23(2):359–361
Mushi AR (2004) Mathematical programming formulations for the examinations timetable problem, the case of the university of Dar es salaam. African Journal Science and Technology, Science and Engineering Series 5:34–40
Papoutsis K, Valouxis C, Housos E (2003) A column generation approach for the timetabling problem of Greek high schools. J Oper Res Soc 54:230–238
Rudová H, Murray K (2003) University course timetabling with soft constraints. In: Burke E, De Causmaecker P (eds) LNCS, vol 2740. Springer, Berlin, pp 310–328
Schaerf A (1999) A survey of automated timetabling. Artif Intell Rev 13 (2):87–127
Schimmelpfeng K, Helber S (2007) Application of a real-world university-course timetabling model solved by integer programming. OR Spectr 29(4):783–803
Tarawneh HY, Ayob M, Ahmad Z (2013) A hybrid simulated annealing with solutions memory for curriculum-based course timetabling problem. J Appl Sci 13:262–269
Tripathy A (1984) School timetabling, a case in large binary integer linear programming. Manag Sci 30:1473–1489
Tripathy A (1992) Computerised decision aid for timetabling - a case analysis. Discret Appl Math 35(3):313–323
Wren A (1996) Scheduling, timetabling and rostering, a special relationship?. LNCS 1153:46–75. Springer, Berlin
Funding
This study has been supported by the University of Rome “Tor Vergata” under grant TRAN.S.S.UM.: Transportation Sustainability and Students’ Urban Mobility: A Multicriteria Approach Through Class Timetabling Optimization.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest
The authors declare that they have no conflict of interest.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Caramia, M., Giordani, S. Curriculum-Based Course Timetabling with Student Flow, Soft Constraints, and Smoothing Objectives: an Application to a Real Case Study. SN Oper. Res. Forum 1, 11 (2020). https://doi.org/10.1007/s43069-020-0013-x
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s43069-020-0013-x