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

Rob van der Mei; Sandjai Bhulai

doi:10.1007/s11134-022-09767-6

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

Rob van der Mei^*
, Sandjai Bhulai

^*Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

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Original language	English
Pages (from-to)	549-551
Number of pages	3
Journal	Queueing Systems
Volume	100
Issue number	3-4
Early online date	28 Mar 2022
DOIs	https://doi.org/10.1007/s11134-022-09767-6
Publication status	Published - Apr 2022

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Funding Information:
This research was supported by the National Science Foundation through award CBET-1464891.

Funding

This research was supported by the National Science Foundation through award CBET-1464891.

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10.1007/s11134-022-09767-6

A data-driven approach to deriving closed-form approximations for queueing problems using genetic algorithmsFinal published version, 241 KBLicence: Article 25fa Dutch Copyright Act

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

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AU - Bhulai, Sandjai

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PY - 2022/4

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JO - Queueing Systems

JF - Queueing Systems

IS - 3-4

ER -

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

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Funding

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