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Methods Using Surrogate Weights

In: Multi-Criteria Decision Making with Partial Preference Information

Author

Listed:
  • Adiel Teixeira de Almeida

    (Federal University of Pernambuco)

  • Eduarda Asfora Frej

    (Federal University of Pernambuco)

  • Lucia Reis Peixoto Roselli

    (Federal University of Pernambuco)

  • Jonatas Araújo de Almeida

    (Federal University of Pernambuco)

  • Ana Paula Cabral Seixas Costa

    (Federal University of Pernambuco)

  • Danielle Costa Morais

    (Federal University of Pernambuco)

Abstract

This chapter presents surrogate weighting techniques and their application in MCDM/A methods using partial preference information, considering both additive models related to Multi-Attribute Value Theory (MAVT) and also outranking methods, with emphasis on the former. Using Surrogate Weights is a useful approach for dealing with situations in which the Decision Maker (DM) either does not want to or is not able to elicit the values of criteria weights. Instead, a minimum amount of information is provided: commonly, the ranking of criteria weights, which may consider in some methods the use of some cardinal information. To conclude, a discussion is entered into about possible advantages and disadvantages of using surrogate weights when solving a multi-criteria decision problem under partial preference information.

Suggested Citation

  • Adiel Teixeira de Almeida & Eduarda Asfora Frej & Lucia Reis Peixoto Roselli & Jonatas Araújo de Almeida & Ana Paula Cabral Seixas Costa & Danielle Costa Morais, 2026. "Methods Using Surrogate Weights," International Series in Operations Research & Management Science, in: Multi-Criteria Decision Making with Partial Preference Information, chapter 5, pages 79-90, Springer.
    • Handle: RePEc:spr:isochp:978-3-032-19284-4_5
    DOI: 10.1007/978-3-032-19284-4_5
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