Adaptive mechanism for schedule arrangement and optimization in socially-empowered professional sports games
- 196 Downloads
World financial crisis has caused a great impact to our daily lives. The price reflects the difficulty not only to transportation but finance status. In this paper, an adaptive scheduling algorithm for professional sports games was proposed, which greatly improved the performance of conventional game-match scheduling results by hybridizing the Tabu Search algorithm and Genetics algorithm. The purpose of this work is to reduce the travelling cost of all teams. The information of famous sports league (e.g. NBA and MLB) was adopted as preliminary experiment data. Using the new method proposed, it is efficient to find better results than approaches developed before. In addition to finding a feasible schedule that meets all the timing restrictions, the problem addressed in this paper has the extra complexity of having the objective of minimizing the travel costs and every team has the balancing number of the games in home. We formalize the scheduling problem into an optimization problem and adopt the concept of evolution strategy, with consideration of sequential events in a socially world, to solve the challenging issue.
KeywordsSports scheduling Recommender system Schedule optimization Social search
This work is partially supported by the National Science Council, Taiwan, under the grants No. “NSC-99-2221-E-240-003”. Miller Chien is appreciated for his assistance on both implementation and experiment.
- 1.Baack T (1996) Evolutionary algorithms in theory and practice. Oxford University Press USGoogle Scholar
- 3.Barone L, While L, Hughes P, Hingston P (2006) Fixture-scheduling for the australian football league using a multi-objective evolutionary algorithm. IEEE Congress on Evolutionary Computation 3377-3384Google Scholar
- 5.Cooper TB, Kingston JH (1996) “The Complexity of Timetabling Construction Problems,” Practice and Theory of Automated Timetabling, Burke E, Ross P (eds) 281-295Google Scholar
- 8.Davidson J, Steinbreeder J (2000) Hockey For Dummies. John Wiley and SonGoogle Scholar
- 9.Dinitz J, Lamken E, Wallis W (1995) Scheduling a tournament. Handbook of Combinatorial Designs. Dinitz J, Colbourn C (eds) CRC Press 578-584Google Scholar
- 10.Eiben AE, Smith JE (2003) Introduction to evolutionary computing. SpringerGoogle Scholar
- 11.Elshaafi H, Botvich D (2013) Trustworthiness Inference of Multi-tenant Component Services in Service Compositions. J Converg 4(1):31–37Google Scholar
- 13.Gallego D, Huecas G (2012) An Empirical Case of a Context-aware Mobile Recommender System in a Banking Environment. J Converg 3(4):49–56Google Scholar
- 21.McAloon K, Tretkoff C, Wetzel G (1997) Sports League Scheduling, Proceedings of the 1997 ILOG Optimization Suite International Users’ ConferenceGoogle Scholar
- 26.Taylor BW (1999) Introduction to Management Science, 6th edn. Prentice Hall, Upper Saddle RiverGoogle Scholar
- 27.Yang JT, Huang HD, Horng JT (2002) Devising a cost-effective baseball scheduling by evolutionary algorithms. Proc 2002 Congr Evol Comput 2:1660–1665Google Scholar