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Complexity of finding Pareto-efficient allocations of highest welfare

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Listed:
  • Peter Biro

    (Centre for Economic and Regional Studies and Department of Operations Research and Actuarial Sciences, Corvinus University ofBudapest, Hungary)

  • Jens Gudmundsson

    (Department of Food and Resource Economics, University of Copenhagen, Denmark,)

Abstract

We allocate objects to agents as exemplified primarily by school choice. Welfare judgments of the object-allocating agency are encoded as edge weights in the acceptability graph. The welfare of an allocation is the sum of its edge weights. We introduce the constrained welfare-maximizing solution, which is the allocation of highest welfare among the Pareto-efficient allocations. We identify conditions under which this solution is easily determined from a computational point of view. For the unrestricted case, we formulate an integer program and find this to be viable in practice as it quickly solves a real-world instance of kindergarten allocation and large-scale simulated instances. Incentives to report preferences truthfully are discussed briefly.

Suggested Citation

  • Peter Biro & Jens Gudmundsson, 2020. "Complexity of finding Pareto-efficient allocations of highest welfare," CERS-IE WORKING PAPERS 2016, Institute of Economics, Centre for Economic and Regional Studies.
  • Handle: RePEc:has:discpr:2016
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    Cited by:

    1. Eirinakis, Pavlos & Mourtos, Ioannis & Zampou, Eleni, 2022. "Random Serial Dictatorship for horizontal collaboration in logistics," Omega, Elsevier, vol. 111(C).
    2. Hai Nguyen & Thành Nguyen & Alexander Teytelboym, 2021. "Stability in Matching Markets with Complex Constraints," Management Science, INFORMS, vol. 67(12), pages 7438-7454, December.
    3. Richárd Kicsiny & Zoltán Varga, 2023. "New algorithm for checking Pareto optimality in bimatrix games," Annals of Operations Research, Springer, vol. 320(1), pages 235-259, January.
    4. Demeulemeester, Tom & Goossens, Dries & Hermans, Ben & Leus, Roel, 2023. "A pessimist’s approach to one-sided matching," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1087-1099.
    5. Kondratev, Aleksei Y. & Nesterov, Alexander S., 2022. "Minimal envy and popular matchings," European Journal of Operational Research, Elsevier, vol. 296(3), pages 776-787.
    6. 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.
    7. Dilek Sayedahmed, 2022. "Centralized refugee matching mechanisms with hierarchical priority classes," The Journal of Mechanism and Institution Design, Society for the Promotion of Mechanism and Institution Design, University of York, vol. 7(1), pages 71-111, December.

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    More about this item

    Keywords

    Assignment; Pareto-efficiency; Welfare-maximization; Complexity; Integerprogrammin;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis

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