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Adaptive mechanism for schedule arrangement and optimization in socially-empowered professional sports games

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Abstract

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.

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References

  1. Baack T (1996) Evolutionary algorithms in theory and practice. Oxford University Press US

  2. Balas E, Saltzman MJ (1991) An algorithm for the three-index assignment problem. Oper Res 39(1):150–161

    Article  MATH  MathSciNet  Google 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 3377-3384

  4. Bean JC, Birge JR (1980) Reducing travelling costs and player fatigue in the national basketball association. Interfaces 10:98–102

    Article  Google Scholar 

  5. Cooper TB, Kingston JH (1996) “The Complexity of Timetabling Construction Problems,” Practice and Theory of Automated Timetabling, Burke E, Ross P (eds) 281-295

  6. Costa D (1995) An Evolutionary Tabu Search Algorithm and the NHL Scheduling Problem. Infor Ottawa 33(3):161–179

    MATH  Google Scholar 

  7. Damon Matthews H, Gillett NP, Stott PA, Zickfeld K (2009) The proportionality of global warming to cumulative carbon emissions. Nature 459:829–832

    Article  Google Scholar 

  8. Davidson J, Steinbreeder J (2000) Hockey For Dummies. John Wiley and Son

  9. Dinitz J, Lamken E, Wallis W (1995) Scheduling a tournament. Handbook of Combinatorial Designs. Dinitz J, Colbourn C (eds) CRC Press 578-584

  10. Eiben AE, Smith JE (2003) Introduction to evolutionary computing. Springer

  11. Elshaafi H, Botvich D (2013) Trustworthiness Inference of Multi-tenant Component Services in Service Compositions. J Converg 4(1):31–37

    Google Scholar 

  12. Frieze AM, Yadegar J (1981) An algorithm for solving 3-dimensional assignment problems with application to scheduling a teaching practice. J Oper Res Soc 32(11):989–995

    Article  MATH  Google 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):49–56

    Google Scholar 

  14. Glover F, Laguna M, Marti R (2000) Fundamentals of scatter search and path relinking. Control Cybern 29(3):653–684

    MATH  MathSciNet  Google Scholar 

  15. Gopalakrishnan A (2013) A subjective job scheduler based on a backpropagation neural network. Hum-Centric Comput Inform Sci 3:17

    Article  Google Scholar 

  16. Henz M (2004) Global constraints for round robin tournament scheduling. Eur J Oper Res 153:92–101

    Article  MATH  MathSciNet  Google Scholar 

  17. Hwang YS, Kwon JB, Moon JC, Cho SJ (2013) Classifying malicious web pages by using an adaptive support vector machine. J Inform Proc Syst 9(3):395–404

    Article  Google Scholar 

  18. Ibrahim N, Mohammad M, Alagar V (2013) Publishing and discovering context-dependent services. Hum-Centric Comput Inform Sci 3:1

    Article  Google Scholar 

  19. Kamal Sarkar K, Nasipuri M, Ghose S (2012) Machine learning based keyphrase extraction: comparing decision trees, naïve bayes, and artificial neural networks. J Inform Proc Syst 8(4):693–712

    Article  Google Scholar 

  20. Magos D (1996) Tabu search for the planar three-index assignment problem. J Glob Optim 8(1):35–48

    Article  MATH  MathSciNet  Google Scholar 

  21. McAloon K, Tretkoff C, Wetzel G (1997) Sports League Scheduling, Proceedings of the 1997 ILOG Optimization Suite International Users’ Conference

  22. Nemhauser GL, Trick MA (1998) Scheduling a major college basketball conference. Oper Res 46(1):1–8

    Article  Google Scholar 

  23. Russell RA, Leung JMY (1994) Devising a cost effective scheduling for a basketball league. Oper Res 42(4):612–625

    Article  Google Scholar 

  24. Saltzman RM, Bradford RM (1996) Optimal realignments of the teams in the national football league. Eur J Oper Res 93:469–475

    Article  MATH  Google Scholar 

  25. Sarchinger T, Heimlich R, Houghton RA, Dong F, Elobeid A, Fabiosa J, Tokgoz S, Hayes D, Yu TH (2008) Use of U.S. croplands for biofuels increases greenhouse gases through emissions from land-use change. Science 319(5867):1238–1240

    Article  Google Scholar 

  26. Taylor BW (1999) Introduction to Management Science, 6th edn. Prentice Hall, Upper Saddle River

    Google Scholar 

  27. Yang JT, Huang HD, Horng JT (2002) Devising a cost-effective baseball scheduling by evolutionary algorithms. Proc 2002 Congr Evol Comput 2:1660–1665

    Google Scholar 

Download references

Acknowledgments

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.

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Correspondence to Neil Y. Yen.

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Hung, J.C., Yen, N.Y., Jeong, HY. et al. Adaptive mechanism for schedule arrangement and optimization in socially-empowered professional sports games. Multimed Tools Appl 74, 5085–5108 (2015). https://doi.org/10.1007/s11042-014-1852-2

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  • DOI: https://doi.org/10.1007/s11042-014-1852-2

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