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Australasian Joint Conference on Artificial Intelligence

AI 2009: AI 2009: Advances in Artificial Intelligence pp 381–390Cite as

Scheduling for the National Hockey League Using a Multi-objective Evolutionary Algorithm

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5866))

Abstract

We describe a multi-objective evolutionary algorithm that derives schedules for the National Hockey League according to three objectives: minimising the teams’ total travel, promoting equity in rest time between games, and minimising long streaks of home or away games. Experiments show that the system is able to derive schedules that beat the 2008–9 NHL schedule in all objectives simultaneously, and that it returns a set of schedules that offer a range of trade-offs across the objectives.

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References

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Author information

Authors and Affiliations

  1. Computer Science & Software Engineering, The University of Western Australia, Australia, 6009

    Sam Craig, Lyndon While & Luigi Barone

Authors
  1. Sam Craig
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  2. Lyndon While
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  3. Luigi Barone
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Editor information

Editors and Affiliations

  1. Clayton School of Information Technology, Monash University, 3800, Clayton, VIC, Australia

    Ann Nicholson

  2. School of Computer Science and Information Technology, RMIT University, 3001, Melbourne, VIC, Australia

    Xiaodong Li

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© 2009 Springer-Verlag Berlin Heidelberg

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Craig, S., While, L., Barone, L. (2009). Scheduling for the National Hockey League Using a Multi-objective Evolutionary Algorithm. In: Nicholson, A., Li, X. (eds) AI 2009: Advances in Artificial Intelligence. AI 2009. Lecture Notes in Computer Science(), vol 5866. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10439-8_39

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  • DOI: https://doi.org/10.1007/978-3-642-10439-8_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10438-1

  • Online ISBN: 978-3-642-10439-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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