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The Evidential Reasoning Approach for Multi-attribute Decision Analysis under Both Fuzzy and Interval Uncertainty

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Interval / Probabilistic Uncertainty and Non-Classical Logics

Part of the book series: Advances in Soft Computing ((AINSC,volume 46))

Summary

Many multiple attribute decision analysis (MADA) problems are characterised by both quantitative and qualitative attributes with various types of uncertainties. Incompleteness (or ignorance) and vagueness (or fuzziness) are among the most common uncertainties in decision analysis. The evidential reasoning (ER) and the interval grade evidential reasoning (IER) approaches have been developed in recent years to support the solution of MADA problems with interval uncertainties and local ignorance in decision analysis. In this paper, the ER approach is enhanced to deal with both interval uncertainty and fuzzy beliefs in assessing alternatives on an attribute. In this newly developed FIER approach, local ignorance and grade fuzziness are modelled under the integrated framework of a distributed fuzzy belief structure, leading to a fuzzy belief decision matrix. A numerical example is provided to illustrate the detailed implementation process of the FIER approach and its validity and applicability.

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Authors and Affiliations

  1. Institute of Systems Engineering Key Laboratory of Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan, China

    Min Guo, Jian-Bo Yang & Hongwei Wang

  2. Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Hong Kong, China

    Kwai-Sang Chin

  3. Manchester Business School, The University of Manchester, UK

    Jian-Bo Yang

Authors
  1. Min Guo
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  2. Jian-Bo Yang
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  3. Kwai-Sang Chin
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  4. Hongwei Wang
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Editor information

Van-Nam Huynh Yoshiteru Nakamori Hiroakira Ono Jonathan Lawry Vkladik Kreinovich Hung T. Nguyen

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© 2008 Springer-Verlag Berlin Heidelberg

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Guo, M., Yang, JB., Chin, KS., Wang, H. (2008). The Evidential Reasoning Approach for Multi-attribute Decision Analysis under Both Fuzzy and Interval Uncertainty. In: Huynh, VN., Nakamori, Y., Ono, H., Lawry, J., Kreinovich, V., Nguyen, H.T. (eds) Interval / Probabilistic Uncertainty and Non-Classical Logics. Advances in Soft Computing, vol 46. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77664-2_11

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  • DOI: https://doi.org/10.1007/978-3-540-77664-2_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77663-5

  • Online ISBN: 978-3-540-77664-2

  • eBook Packages: EngineeringEngineering (R0)

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