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International Conference on Computational Collective Intelligence

ICCCI 2016: Computational Collective Intelligence pp 335–344Cite as

Cost Optimizing Methods for Deterministic Queuing Systems

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9875))

Abstract

The paper discusses two proposed methods for the cost optimization of the deterministic queuing system based on the control of the queue lengths. The first method uses the evaluation of actual states at the particular service places according to their development. The decision is then based on the comparison of the criteria of productivity and the expended costs. The suggested change in the system setting with the highest priority is then accomplished. The second method is based on the simulation of the future states and on this basis the appropriate time and type of the modification of the system setup is suggested.

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References

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Acknowledgments

The support of the Specific research project at FIM UHK and Czech Science Foundation project Nr. 14-02424S is gratefully acknowledged.

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Authors and Affiliations

  1. Faculty of Informatics and Management, University of Hradec Králové, Rokitanského 62, 50003, Hradec Králové, Czech Republic

    Martin Gavalec & Zuzana Němcová

Authors
  1. Martin Gavalec
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  2. Zuzana Němcová
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Corresponding author

Correspondence to Zuzana Němcová .

Editor information

Editors and Affiliations

  1. Wrocław University of Technology, Wrocław, Poland

    Ngoc-Thanh Nguyen

  2. Aristotle University of Thessaloniki, Thessaloniki, Greece

    Lazaros Iliadis

  3. Department of Forestry and Management, Democritus University of Thrace, Orestiada, Thrace, Greece

    Yannis Manolopoulos

  4. Wrocław University of Technology, Wrocław, Poland

    Bogdan Trawiński

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© 2016 Springer International Publishing Switzerland

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Cite this paper

Gavalec, M., Němcová, Z. (2016). Cost Optimizing Methods for Deterministic Queuing Systems. In: Nguyen, NT., Iliadis, L., Manolopoulos, Y., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2016. Lecture Notes in Computer Science(), vol 9875. Springer, Cham. https://doi.org/10.1007/978-3-319-45243-2_31

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  • DOI: https://doi.org/10.1007/978-3-319-45243-2_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45242-5

  • Online ISBN: 978-3-319-45243-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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