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An approximation to max min fairness in multi commodity networks

Author

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  • Hamoud S. Bin Obaid

    (University of Oklahoma
    King Saud University)

  • Theodore B. Trafalis

    (University of Oklahoma)

Abstract

The two objectives of max min fairness (MMF) in multi commodity networks are maximizing the overall throughput so the network operator is satisfied when network is utilized, and minimizing the overall difference in throughput between commodities satisfying the users with fair bandwidth allocation. These two objectives are conflicting, so are translated into a bi-objective model where throughput is maximized in one objective, and the difference in flow between commodities is minimized in the other objective. The proposed approach in this paper is meant to handle large scale networks since the common approaches are feasible only on small to medium scale networks. Although the solution is an approximation to MMF, but it can be exact to the MMF solution when ɛ is properly selected. An illustrative example is discussed in addition to experimentations on real and random networks. The experimentations show the effectiveness of the proposed model.

Suggested Citation

  • Hamoud S. Bin Obaid & Theodore B. Trafalis, 2020. "An approximation to max min fairness in multi commodity networks," Computational Management Science, Springer, vol. 17(1), pages 65-77, January.
    • Handle: RePEc:spr:comgts:v:17:y:2020:i:1:d:10.1007_s10287-018-0336-7
    DOI: 10.1007/s10287-018-0336-7
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    References listed on IDEAS

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    1. Philip D. Leclerc & Laura A. McLay & Maria E. Mayorga, 2012. "Modeling Equity for Allocating Public Resources," International Series in Operations Research & Management Science, in: Michael P. Johnson (ed.), Community-Based Operations Research, chapter 0, pages 97-118, Springer.
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    Cited by:

    1. Khodakaram Salimifard & Sara Bigharaz, 2022. "The multicommodity network flow problem: state of the art classification, applications, and solution methods," Operational Research, Springer, vol. 22(1), pages 1-47, March.

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