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Fairness in Resource Allocation: Foundation and Applications

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Network Algorithms, Data Mining, and Applications (NET 2018)

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Abstract

This paper presents a comprehensive review of fairness in resource allocation and its foundation. Fairness is applied when the resources divided on multiple demands are limited. Implementing fairness in resource allocation is a challenging task since fairness and efficiency are contradicting objectives. A variety of approaches to find fair resource allocation from the literature are discussed such as max-min fairness, lexicographic ordering, proportional fairness in addition to some fairness measures. Both strength points and drawbacks for each approach are illustrated, and some connections among the approaches are elaborated. Examples of applications where fairness is applied are reviewed.

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Acknowledgements

Dr. Theodore Trafalis was supported by RSF Grant 14-41-00039, and he conducted research at National Research University Higher School of Economics.

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Authors and Affiliations

  1. University of Oklahoma, 202 W. Boyd St., Lab 28, Norman, OK, 73071, USA

    Hamoud S. Bin-Obaid & Theodore B. Trafalis

  2. King Saud University, 800, Riyadh, 11421, Saudi Arabia

    Hamoud S. Bin-Obaid

Authors
  1. Hamoud S. Bin-Obaid
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  2. Theodore B. Trafalis
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Corresponding author

Correspondence to Hamoud S. Bin-Obaid .

Editor information

Editors and Affiliations

  1. Higher School of Economics, National Research University, Nizhny Novgorod, Russia

    Ilya Bychkov

  2. Higher School of Economics, National Research University, Nizhny Novgorod, Russia

    Valery A. Kalyagin

  3. Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

  4. Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, PA, USA

    Oleg Prokopyev

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Bin-Obaid, H.S., Trafalis, T.B. (2020). Fairness in Resource Allocation: Foundation and Applications. In: Bychkov, I., Kalyagin, V., Pardalos, P., Prokopyev, O. (eds) Network Algorithms, Data Mining, and Applications. NET 2018. Springer Proceedings in Mathematics & Statistics, vol 315. Springer, Cham. https://doi.org/10.1007/978-3-030-37157-9_1

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