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Modeling and analysis of flexible queueing systems

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  • Suri Gurumurthi
  • Saif Benjaafar

Abstract

We consider queueing systems with multiple classes of customers and heterogeneous servers where customers have the flexibility of being processed by more than one server and servers possess the capability of processing more than one customer class. We provide a unified framework for the modeling and analysis of these systems under arbitrary customer and server flexibility and for a rich set of control policies that includes customer/server‐specific priority schemes for server and customer selection. We use our models to generate several insights into the effect of system configuration and control policies. In particular, we examine the relationship between flexibility, control policies and throughput under varying assumptions for system parameters. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004

Suggested Citation

  • Suri Gurumurthi & Saif Benjaafar, 2004. "Modeling and analysis of flexible queueing systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(5), pages 755-782, August.
    • Handle: RePEc:wly:navres:v:51:y:2004:i:5:p:755-782
    DOI: 10.1002/nav.20020
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    References listed on IDEAS

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    3. Kim, Nayeon & Montreuil, Benoit & Klibi, Walid & Zied Babai, M., 2023. "Network inventory deployment for responsive fulfillment," International Journal of Production Economics, Elsevier, vol. 255(C).
    4. Naumov, Valeriy & Martikainen, Olli, 2011. "Method for Throughput Maximization of Multiclass Networks with Flexible Servers," Discussion Papers 1261, The Research Institute of the Finnish Economy.
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    6. Naumov, Valeriy & Martikainen, Olli, 2011. "Optimal Resource Allocation in Multiclass Networks," Discussion Papers 1262, The Research Institute of the Finnish Economy.
    7. Sigrún Andradóttir & Hayriye Ayhan & Douglas G. Down, 2007. "Compensating for Failures with Flexible Servers," Operations Research, INFORMS, vol. 55(4), pages 753-768, August.
    8. Kenneth C. Chong & Shane G. Henderson & Mark E. Lewis, 2016. "The Vehicle Mix Decision in Emergency Medical Service Systems," Manufacturing & Service Operations Management, INFORMS, vol. 18(3), pages 347-360, July.
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    12. Xi Chen & Jiawei Zhang & Yuan Zhou, 2015. "Optimal Sparse Designs for Process Flexibility via Probabilistic Expanders," Operations Research, INFORMS, vol. 63(5), pages 1159-1176, October.
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    14. Fiorotto, Diego Jacinto & Jans, Raf & Alexandre de Araujo, Silvio, 2018. "Process flexibility and the chaining principle in lot sizing problems," International Journal of Production Economics, Elsevier, vol. 204(C), pages 244-263.
    15. Timothy C. Y. Chan & Daniel Letourneau & Benjamin G. Potter, 2022. "Sparse flexible design: a machine learning approach," Flexible Services and Manufacturing Journal, Springer, vol. 34(4), pages 1066-1116, December.
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