Abstract
Our paper presents a new exact method to solve the traveling tournament problem. More precisely, we apply DFS* to this problem and improve its performance by keeping the expensive heuristic estimates in memory to help greatly cut down the computational time needed. We further improve the performance by exploiting a symmetry property found in the traveling tournament problem. Our results show that our approach is one of the top performing approaches for this problem. It is able to find known optimal solutions in a much smaller amount of computational time than past approaches, to find a new optimal solution, and to improve the lower bounds of larger problem instances which do not have known optimal solutions. As a final contribution, we also introduce a new set of problem instances to diversify the available instance sets for the traveling tournament problem.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Benoist, T., Laburthe, F., Rottembourg, B.: Lagrange relaxation and constraint programming collaborative schemes for travelling tournament problems. In: Proceedings of CP-AI-OR 2001, Wye College, UK, pp. 15–26 (2001)
Dechter, R.: Constraint Processing. Morgan Kaufmann Publishers, San Francisco (2003)
Easton, K., Nemhauser, G., Trick, M.: The traveling tournament problem description and benchmarks. In: Walsh, T. (ed.) CP 2001. LNCS, vol. 2239, pp. 580–584. Springer, Heidelberg (2001)
Easton, K., Nemhauser, G., Trick, M.: Solving the travelling tournament problem: A combined integer programming and constraint programming approach. In: Burke, E.K., De Causmaecker, P. (eds.) PATAT 2002. LNCS, vol. 2740, pp. 100–109. Springer, Heidelberg (2003)
Irnich, S., Schrempp, U.: A new branch-and-price algorithm for the traveling tournament problem. Presented at Column Generation 2008, Aussois, France (June 17-20, 2008), http://www.gerad.ca/colloques/ColumnGeneration2008/slides/SIrnich.pdf (accessed March 07, 2009)
Sarkar, U.K., Chakrabarti, P.P., Ghose, S., De Sarkar, S.C.: Reducing reexpansions in iterative-deepening search by controlling cutoff bounds. Artificial Intelligence 50, 207–221 (1991)
Trick, M.: Challenge Traveling Tournament Problems, http://mat.gsia.cmu.edu/TOURN/ (accessed March 07, 2009)
Urrutia, S., Ribeiro, C.C., Melo, R.A.: A new lower bound to the traveling tournament problem. In: IEEE Symposium on Computational Intelligence in Scheduling, pp. 15–18 (2007)
Vempaty, N.R., Kumar, V., Korf, R.E.: Depth-First vs Best-First Search. In: Proc. National Conf. on Artificial Intelligence, AAAI 1991, Anaheim, CA, pp. 434–440 (1991)
Wah, B.W.: MIDA*: An IDA* search with dynamic control. Technical report, Coordinated Science Laboratoy, University of Illinois, Urbana, Illinois (1991)
Talbi, E.-G.: Parallel Combinatorial Optimization. John Wiley & Sons, Hoboken (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Uthus, D.C., Riddle, P.J., Guesgen, H.W. (2009). DFS* and the Traveling Tournament Problem. In: van Hoeve, WJ., Hooker, J.N. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2009. Lecture Notes in Computer Science, vol 5547. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01929-6_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-01929-6_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01928-9
Online ISBN: 978-3-642-01929-6
eBook Packages: Computer ScienceComputer Science (R0)