Abstract
The Balanced Academic Curriculum Problem (BACP) consists in assigning courses to teaching periods satisfying prerequisites and balancing students’ load. BACP is included in CSPlib along with three benchmark instances. However, the BACP formulation in CSPLib is actually simpler than the real problem that, in general, universities have to solve in practice.
In this paper, we propose a generalized formulation of the problem and we study a set of hybrid solution techniques based on high-level control strategies that drive a collection of basic local search components. The result of the study allows us to build a complex combination of simulated annealing, dynamic tabu search and large-neighborhood search. In addition, we present six new instances obtained from our university, which are much larger and more challenging than the CSPlib ones (the latter are always solved to optimality in less than 0.1 seconds by our techniques).
For the sake of possible future comparisons, we make available through the web all the input data, our scores and results, and a solution validator.
This is a preview of subscription content, log in via an institution to check access.
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
Ahuja, R., Ergun, Ö., Orlin, J., Punnen, A.: A survey of very-large-scale neighborhood search techniques. Discrete Applied Mathematics 123, 75–102 (2002)
Castro, C., Crawford, B., Monfroy, E.: A quantitative approach for the design of academic curricula. In: Smith, M.J., Salvendy, G. (eds.) HCII 2007. LNCS, vol. 4558, pp. 279–288. Springer, Heidelberg (2007)
Castro, C., Manzano, S.: Variable and value ordering when solving balanced academic curriculum problems. In: 6th Workshop of the ERCIM WG on Constraints (2001)
Di Gaspero, L., McCollum, B., Schaerf, A.: The second international timetabling competition (ITC-,: Curriculum-based course timetabling (track 3). Technical Report QUB/IEEE/Tech/ITC2007/CurriculumCTT/v1.0/1, School of Electronics, Electrical Engineering and Computer Science, Queens University, Belfast (UK). ITC-2007 (August 2007), http://www.cs.qub.ac.uk/itc2007/
Di Gaspero, L., Schaerf, A.: EasyLocal++: An object-oriented framework for flexible design of local search algorithms. Software—Practice and Experience 33(8), 733–765 (2003)
Di Gaspero, L., Schaerf, A.: Neighborhood portfolio approach for local search applied to timetabling problems. Journal of Mathematical Modeling and Algorithms 5(1), 65–89 (2006)
Gent, I.P., Walsh, T.: CSPLib: a benchmark library for constraints. Technical report, Technical report APES-09-1999 (1999), http://csplib.cs.strath.ac.uk/ ; A shorter version appears. In: The Proceedings of the 5th International Conference on Principles and Practices of Constraint Programming (CP 1999). LNCS, vol. 1713, pp. 480–481. Springer, Heidelberg (1999)
Hansen, P., Mladenović, N.: An introduction to variable neighbourhood search. In: Voß, S., Martello, S., Osman, I.H., Roucairol, C. (eds.) Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization, pp. 433–458. Kluwer Academic Publishers, Dordrecht (1999)
Hnich, B., Kızıltan, Z., Walsh, T.: Modelling a balanced academic curriculum problem. In: CP-AI-OR 2002, pp. 121–131 (2002)
Hoos, H.H., Stützle, T.: Stochastic Local Search – Foundations and Applications. Morgan Kaufmann Publishers, San Francisco (2005)
Lambert, T., Castro, C., Monfroy, E., Saubion, F.: Solving the balanced academic curriculum problem with an hybridization of genetic algorithm and constraint propagation. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds.) ICAISC 2006. LNCS (LNAI), vol. 4029, pp. 410–419. Springer, Heidelberg (2006)
Lourenço, H.R., Martin, O., Stützle, T.: Applying iterated local search to the permutation flow shop problem. In: Glover, F., Kochenberger, G. (eds.) Handbook of Metaheuristics. Kluwer, Dordrecht (2001)
Schaerf, A., Di Gaspero, L.: Measurability and reproducibility in timetabling research: Discussion and proposals. In: Burke, E., Rudová, H. (eds.) PATAT 2007. LNCS, vol. 3867, pp. 40–49. Springer, Heidelberg (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Di Gaspero, L., Schaerf, A. (2008). Hybrid Local Search Techniques for the Generalized Balanced Academic Curriculum Problem. In: Blesa, M.J., et al. Hybrid Metaheuristics. HM 2008. Lecture Notes in Computer Science, vol 5296. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88439-2_11
Download citation
DOI: https://doi.org/10.1007/978-3-540-88439-2_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88438-5
Online ISBN: 978-3-540-88439-2
eBook Packages: Computer ScienceComputer Science (R0)