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An axiomatization of the Euclidean compromise solution

Author

Listed:
  • Voorneveld, Mark

    (Dept. of Economics, Stockholm School of Economics)

  • van den Nouweland, Anne

    (Department of Economics, University of Oregon)

  • McLean, Rich

    (Department of Economics, Rutgers University)

Abstract

The utopia point of a multicriteria optimization problem is the vector that specifies for each criterion the most favourable among the feasible values. The Euclidean compromise solution in multicriteria optimization is a solution concept that assigns to a feasible set the alternative with minimal Euclidean distance to the utopia point. The purpose of this paper is to provide a characterization of the Euclidean compromise solution. Consistency plays a crucial role in our approach.

Suggested Citation

  • Voorneveld, Mark & van den Nouweland, Anne & McLean, Rich, 2008. "An axiomatization of the Euclidean compromise solution," SSE/EFI Working Paper Series in Economics and Finance 703, Stockholm School of Economics.
  • Handle: RePEc:hhs:hastef:0703
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    References listed on IDEAS

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    Cited by:

    1. William Thomson, 2022. "On the axiomatic theory of bargaining: a survey of recent results," Review of Economic Design, Springer;Society for Economic Design, vol. 26(4), pages 491-542, December.
    2. Büsing, Christina & Goetzmann, Kai-Simon & Matuschke, Jannik & Stiller, Sebastian, 2017. "Reference points and approximation algorithms in multicriteria discrete optimization," European Journal of Operational Research, Elsevier, vol. 260(3), pages 829-840.
    3. Christian Roessler, 2006. "Public Good Menus and Feature Complementarity," Department of Economics - Working Papers Series 962, The University of Melbourne.

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    More about this item

    Keywords

    Consistency; Euclidean compromise solution; Multicriteria optimization;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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