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A data-driven approach to deriving closed-form approximations for queueing problems using genetic algorithms

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  • Rob Mei

    (CWI, Stochastics group)

  • Sandjai Bhulai

    (Vrije Universiteit Amsterdam)

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  • Rob Mei & Sandjai Bhulai, 2022. "A data-driven approach to deriving closed-form approximations for queueing problems using genetic algorithms," Queueing Systems: Theory and Applications, Springer, vol. 100(3), pages 549-551, April.
    • Handle: RePEc:spr:queues:v:100:y:2022:i:3:d:10.1007_s11134-022-09767-6
    DOI: 10.1007/s11134-022-09767-6
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    References listed on IDEAS

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    1. I. M. Verloop & U. Ayesta & R. Núñez-Queija, 2011. "Heavy-Traffic Analysis of a Multiple-Phase Network with Discriminatory Processor Sharing," Operations Research, INFORMS, vol. 59(3), pages 648-660, June.
    2. Hamed Taherdoost, 2016. "Sampling Methods in Research Methodology; How to Choose a Sampling Technique for Research," Post-Print hal-02546796, HAL.
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    Cited by:

    1. Opher Baron & Dmitry Krass & Arik Senderovich & Eliran Sherzer, 2024. "Supervised ML for Solving the GI / GI /1 Queue," INFORMS Journal on Computing, INFORMS, vol. 36(3), pages 766-786, May.

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