Scheduling English Football Fixtures: Consideration of Two Conflicting Objectives
In previous work the distance travelled by UK football clubs, and their supporters, over the Christmas/New Year period was minimised. This is important as it is not only a holiday season but, often, there is bad weather at this time of the year. Whilst searching for good quality solutions for this problem, various constraints have to be respected. One of these relates to clashes, which measures how many paired teams play at home on the same day. Whilst the supporters have an interest in minimising the distance they travel, the police also have an interest in having as few pair clashes as possible. This is due to the fact that these fixtures are more expensive, and difficult, to police. However, these two objectives (minimise distance and minimise pair clashes) conflict with one another in that a decrease in one intuitively leads to an increase in the other. This chapter explores this question and shows that there are compromise solutions which allow fewer pair clashes but does not statistically increase the distance travelled. We present a detailed set of computational experiments, on datasets covering seven seasons. We conclude that it is sometimes possible to reduce the number of pair clashes whilst not significantly increasing the overall distance that is travelled.
KeywordsLocal Search Major League Baseball Operational Research Society Good Quality Solution Home Team
Unable to display preview. Download preview PDF.
- 1.Aarts, E., Korst, J., Michels, W.: Simulated annealing. In: Burke, E.K., Kendall, G. (eds.) Search Methodologies: Introductory Tutorials in Optimization and Decision Support Methodologies, 1st edn., ch. 7, pp. 97–125. Springer (2005)Google Scholar
- 5.Cain, W.O.: The computer-aided heuristic approach used to schedule the major league baseball clubs. In: Ladany, S.P., Machol, R.E. (eds.) Optimal Strategies in Sports, pp. 33–41. North Holland, Amsterdam (1977)Google Scholar
- 6.Campbell, R.T., Chen, D.S.: A minimum distance basketball scheduling problem. In: Machol, R.E., Ladany, S.P., Morrison, D.G. (eds.) Management Science in Sports. Studies in the Management Sciences, vol. 4, pp. 15–25. North-Holland, Amsterdam (1976)Google Scholar
- 9.Dinitz, J.H., Fronček, D., Lamken, E.R., Wallis, W.D.: Scheduling a tournament. In: Colbourn, C.J., Dinitz, J.H. (eds.) Handbook of Combinatorial Designs, 2nd edn., pp. 591–606. CRC Press (2006)Google Scholar
- 13.Easton, K., Nemhauser, G.L., Trick, M.A.: Sports scheduling. In: Leung, J.T. (ed.) Handbook of Scheduling, pp. 52.1–52.19. CRC Press (2004)Google Scholar
- 16.Ferland, J.A., Fleurent, C.: Computer aided scheduling for a sport league. INFOR 29, 14–25 (1991)Google Scholar
- 19.Kendall, G., While, L., McCollum, B., Cruz, F.: A multiobjective approach for UK football scheduling. In: Burke, E.K., Gendreau, M. (eds.) Proceedings of the 7th International Conference on the Practice and Theory of Automated Timetabling (2008)Google Scholar
- 20.Knust, S.: Classification of literature on sports scheduling (2010), http://www.inf.uos.de/knust/sportssched/sportlit_class/ (last visited July 15, 2010)
- 23.Trick, M.: Traveling tournament problem instances (2010), http://mat.gsia.cmu.edu/TOURN/ (last accessed July 15, 2010)
- 28.Wright, M.: Timetabling county cricket fixtures using a form of tabu search. Journal of the Operational Research Society 45, 758–770 (1994)Google Scholar