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The K-server problem via a modern optimization lens

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  • Bertsimas, Dimitris
  • Jaillet, Patrick
  • Korolko, Nikita

Abstract

We consider the well-known K-server problem from the perspective of mixed integer, robust and adaptive optimization. We propose a new tractable mixed integer linear formulation of the K-server problem that incorporates both information from the past and uncertainty about the future. By combining ideas from classical online algorithms developed in the computer science literature and robust and adaptive optimization developed in the operations research literature we propose a new method that (a) is computationally tractable, (b) almost always outperforms all other methods in numerical experiments, and (c) is stable with respect to potential errors in the assumptions about the future.

Suggested Citation

  • Bertsimas, Dimitris & Jaillet, Patrick & Korolko, Nikita, 2019. "The K-server problem via a modern optimization lens," European Journal of Operational Research, Elsevier, vol. 276(1), pages 65-78.
    • Handle: RePEc:eee:ejores:v:276:y:2019:i:1:p:65-78
    DOI: 10.1016/j.ejor.2018.12.044
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    References listed on IDEAS

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    1. Tomislav Rudec & Alfonzo Baumgartner & Robert Manger, 2013. "A fast work function algorithm for solving the k-server problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(1), pages 187-205, January.
    2. Miles Lubin & Iain Dunning, 2015. "Computing in Operations Research Using Julia," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 238-248, May.
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    Cited by:

    1. Bakker, Hannah & Dunke, Fabian & Nickel, Stefan, 2020. "A structuring review on multi-stage optimization under uncertainty: Aligning concepts from theory and practice," Omega, Elsevier, vol. 96(C).

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