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Basic Structure for Using Partial Preference Information in MCDM/A

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)

  • Jônatas Araújo de Almeida

    (Federal University of Pernambuco)

  • Ana Paula Cabral Seixas Costa

    (Federal University of Pernambuco)

  • Danielle Costa Morais

    (Federal University of Pernambuco)

Abstract

In the MCDM/A area, methods that use partial preference information have high potential for being applied in the practice of decision making/aiding, since partial/incomplete preference information is easier to express and less cognitively demanding for DMs to define compared to traditional approaches. These reasons may contribute to the popularity of such methods. This chapter aims to present the structural basis of partial preference information methods and their features. Setting out from what motivates the development of these methods, the chapter presents a complete structured framework for partial information methods, considering possibilities for dealing with the preferences modeling process, different forms of partial information that can be provided by the DM, and synthesis steps that can be applied to derive a recommendation. Finally, this chapter presents basic concepts related to the weight space associated with the analysis of DM’s preferential information and how some approaches seek conclusions based on the partial information collected.

Suggested Citation

  • Adiel Teixeira de Almeida & Eduarda Asfora Frej & Lucia Reis Peixoto Roselli & Jônatas Araújo de Almeida & Ana Paula Cabral Seixas Costa & Danielle Costa Morais, 2026. "Basic Structure for Using Partial Preference Information in MCDM/A," International Series in Operations Research & Management Science, in: Multi-Criteria Decision Making with Partial Preference Information, chapter 4, pages 61-75, Springer.
    • Handle: RePEc:spr:isochp:978-3-032-19284-4_4
    DOI: 10.1007/978-3-032-19284-4_4
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