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Postoptimal analysis in a multi-attribute decision model for restoring contaminated aquatic ecosystems

Author

Listed:
  • A Mateos

    (Madrid Technical University)

  • S Ríos-Insua

    (Madrid Technical University)

  • E Gallego

    (Madrid Technical University)

Abstract

We describe the evaluation module of the MOIRA system, developed to identify optimal remedial strategies for restoring radionuclide contaminated aquatic ecosystems and drainage areas. This module includes a multiparametric sensitivity analysis, which is based on a multi-attribute additive value model, aimed at identifying optimal remedial strategies for restoring aquatic ecosystems contaminated by radionuclides. We introduce the sensitivity analysis to check the robustness of the conclusions on the inputs. This provides insights into the problem in the sense of making better use of the available information. This analysis is focused on judgemental inputs, imprecise value functions on attributes and imprecise scaling factors or weights for their aggregation. These are of utmost importance in determining the optimal countermeasures.

Suggested Citation

  • A Mateos & S Ríos-Insua & E Gallego, 2001. "Postoptimal analysis in a multi-attribute decision model for restoring contaminated aquatic ecosystems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(7), pages 727-738, July.
    • Handle: RePEc:pal:jorsoc:v:52:y:2001:i:7:d:10.1057_palgrave.jors.2601156
    DOI: 10.1057/palgrave.jors.2601156
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    Cited by:

    1. Roger Chapman Burk & Richard M. Nehring, 2023. "An Empirical Comparison of Rank-Based Surrogate Weights in Additive Multiattribute Decision Analysis," Decision Analysis, INFORMS, vol. 20(1), pages 55-72, March.
    2. A Mateos & S Ríos-Insua & A Jiménez, 2007. "Dominance, potential optimality and alternative ranking in imprecise multi-attribute decision making," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(3), pages 326-336, March.

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