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Using Fuzzy Measures to Construct Multi-criteria Decision Functions

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Book cover Soft Computing Based Optimization and Decision Models

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 360))

Abstract

We are interested in the formulation of multi-criteria decision functions based on the use of a measure over the space of criteria. Specifically the relationship between the criteria is expressed using a fuzzy measure. We then use the Choquet integral to construct decision functions based on the measure. We look at a number of different decision functions generated from specific classes of measures.

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Author information

Authors and Affiliations

  1. Machine Intelligence Institute, Iona College, New Rochelle, NY, 10801, USA

    Ronald R. Yager

Authors
  1. Ronald R. Yager
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Correspondence to Ronald R. Yager .

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Editors and Affiliations

  1. Department of Computer Science and A.I. Higher Technical School of Information Technology and Telecommunications Engineering, University of Granada, Granada, Spain

    David A. Pelta

  2. Department of Computer Science and A.I. Higher Technical School of Information Technology and Telecommunications Engineering, University of Granada , Granada, Spain

    Carlos Cruz Corona

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Yager, R.R. (2018). Using Fuzzy Measures to Construct Multi-criteria Decision Functions. In: Pelta, D., Cruz Corona, C. (eds) Soft Computing Based Optimization and Decision Models. Studies in Fuzziness and Soft Computing, vol 360. Springer, Cham. https://doi.org/10.1007/978-3-319-64286-4_14

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  • DOI: https://doi.org/10.1007/978-3-319-64286-4_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64285-7

  • Online ISBN: 978-3-319-64286-4

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