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Improving fairness in ambulance planning by time sharing

Author

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  • Jagtenberg, C.J.
  • Mason, A.J.

Abstract

Most literature on the ambulance location problem aims to maximize coverage, i.e., the fraction of people that can be reached within a certain response time threshold. Such a problem often has one optimum, but several near-optimal solutions may exist. These may have a similar overall performance but provide different coverage for different regions. This raises the question: are we making ‘arbitrary’ choices in terms of who gets coverage and who does not? In this paper we propose to share time between several good ambulance configurations in the interest of fairness. We argue that the Bernoulli–Nash social welfare measure should be used to evaluate the fairness of the system. Therefore, we formulate a nonlinear optimization model that determines the fraction of time spent in each configuration to maximize the Bernoulli–Nash social welfare. We solve this model in a case study for an ambulance provider in the Netherlands, using a combination of simulation and optimization. Furthermore, we analyze how the Bernoulli–Nash optimal solution compares to the maximum-coverage solution by formulating and solving a multi-objective optimization model.

Suggested Citation

  • Jagtenberg, C.J. & Mason, A.J., 2020. "Improving fairness in ambulance planning by time sharing," European Journal of Operational Research, Elsevier, vol. 280(3), pages 1095-1107.
    • Handle: RePEc:eee:ejores:v:280:y:2020:i:3:p:1095-1107
    DOI: 10.1016/j.ejor.2019.08.003
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    Citations

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    Cited by:

    1. Reuter-Oppermann, Melanie & Wolff, Clemens & Pumplun, Luisa, 2021. "Next Frontiers in Emergency Medical Services in Germany: Identifying Gaps between Academia and Practice," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 124665, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    2. Aziz, Haris & Huang, Xin & Mattei, Nicholas & Segal-Halevi, Erel, 2023. "Computing welfare-Maximizing fair allocations of indivisible goods," European Journal of Operational Research, Elsevier, vol. 307(2), pages 773-784.
    3. Akdogan, M. Altan & Bayındır, Z. Pelin & Iyigun, Cem, 2023. "An analysis of ambulance location problem from an equity perspective," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    4. Akoluk, Damla & Karsu, Özlem, 2022. "Ensuring multidimensional equality in public service," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    5. Xia Chen & Yucheng Dong & Ying He, 2024. "Group Risky Choice and Resource Allocation Under Social Comparison Effects," Group Decision and Negotiation, Springer, vol. 33(5), pages 977-1017, October.
    6. Argyris, Nikolaos & Karsu, Özlem & Yavuz, Mirel, 2022. "Fair resource allocation: Using welfare-based dominance constraints," European Journal of Operational Research, Elsevier, vol. 297(2), pages 560-578.
    7. Qing Feng & Dengfeng Li & Guichuan Zhou & Zhibin Wu, 2024. "Fairness based unique common equilibrium efficient frontier for evaluating decision-making units with fixed-sum outputs," Annals of Operations Research, Springer, vol. 341(1), pages 427-449, October.

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