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A Robustness Study of State-of-the-Art Surrogate Weights for MCDM

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  • Mats Danielson

    (Stockholm University
    International Institute for Applied Systems Analysis, IIASA)

  • Love Ekenberg

    (Stockholm University
    International Institute for Applied Systems Analysis, IIASA)

Abstract

A vast number of methods for solving multi-criteria decision problems have been suggested for assessing criteria weights requiring more exact input data than users normally are able to provide. In particular, the selection of adequate criteria weights is difficult and in order to be realistic, other methods must be introduced. One class of such methods is to introduce so called surrogate weights, where numerical weights are assigned to each criterion based on a cardinal or ordinal rank ordering, assumed to represent the information extracted from the user. One essential problem is the robustness of such methods. In this article, we compare state-of-the-art methods based on surrogate weights from the literature and, utilising a simulation approach, discuss underlying assumptions and robustness properties. This results in a quantitative measurement of these weighting methods and a methodology applicable also to forthcoming methods.

Suggested Citation

  • Mats Danielson & Love Ekenberg, 2017. "A Robustness Study of State-of-the-Art Surrogate Weights for MCDM," Group Decision and Negotiation, Springer, vol. 26(4), pages 677-691, July.
  • Handle: RePEc:spr:grdene:v:26:y:2017:i:4:d:10.1007_s10726-016-9494-6
    DOI: 10.1007/s10726-016-9494-6
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    References listed on IDEAS

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    Cited by:

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    5. Mehmet Ali Dereli & Emre Tercan, 2021. "Comparison of GIS-based surrogate weighting methods for multi-directional landfill site selection in West Mediterranean Planning Region in Turkey," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(3), pages 3438-3457, March.
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    7. Ewa Roszkowska, 2020. "The extention rank ordering criteria weighting methods in fuzzy enviroment," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 30(2), pages 91-114.
    8. Joanna Jaroszewicz & Anna Majewska, 2021. "Group Spatial Preferences of Residential Locations—Simplified Method Based on Crowdsourced Spatial Data and MCDA," Sustainability, MDPI, vol. 13(9), pages 1-24, April.

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