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Improving the Elicitation Process for Intra-criterion Evaluation in the FITradeoff Method

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Innovation for Systems Information and Decision (INSID 2021)

Abstract

With the advance coming from studies in the area of decision making, different models have emerged to assist in the interpretation of multicriteria decision problems. One of the most recent improvements in the MCDM/A mathematical models deals with the use of partial information about the preferences of the decision makers at the elicitation process. The FITradeoff method is a MAVT (Multi-attribute Value Theory) method that requires only strict preferences and uses partial information in judgments, reducing the amount of information required. Therefore, this study aims to improve the intra-criteria evaluation step of the FITradeoff method, by proposing a new approach for elicitation of marginal value functions based on partial information. The proposed approach is based on the traditional bisection method, but requires preference statements only. The results obtain show that the approach using the bisection method associated with the use of partial information appears to have a good performance, enabling the improvement of the process in terms of reducing the effort and time required.

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Acknowledgment

The authors are grateful for the support received and the funding provided by the Coordination for the Improvements of Higher Education Personnel (CAPES).

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Correspondence to Paolla Polla Pontes do Espírito Santo .

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Santo, P.P.P.d.E., Frej, E.A., de Almeida, A.T. (2021). Improving the Elicitation Process for Intra-criterion Evaluation in the FITradeoff Method. In: de Almeida, A.T., Morais, D.C. (eds) Innovation for Systems Information and Decision. INSID 2021. Lecture Notes in Business Information Processing, vol 435. Springer, Cham. https://doi.org/10.1007/978-3-030-91768-5_5

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  • DOI: https://doi.org/10.1007/978-3-030-91768-5_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-91767-8

  • Online ISBN: 978-3-030-91768-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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