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Pacific Rim International Conference on Artificial Intelligence

PRICAI 2012: PRICAI 2012: Trends in Artificial Intelligence pp 297–311Cite as

A D-S Theory Based AHP Decision Making Approach with Ambiguous Evaluations of Multiple Criteria

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7458))

Abstract

This paper proposes an ambiguity aversion principle of minimax regret to extend DS/AHP approach of multi-criteria decision making (MCDM). This extension can analyze the MCDM problems with ambiguous evaluations of multiple criteria. Such evaluations cannot be avoided in real life, but that existing MCDM theories and models cannot handle it well. We also give an example of real estate investment to illustrate our approach.

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Author information

Authors and Affiliations

  1. Institute of Logic and Cognition, Sun Yat-Sen University, Guangzhou, 510275, China

    Wenjun Ma, Wei Xiong & Xudong Luo

Authors
  1. Wenjun Ma
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  2. Wei Xiong
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  3. Xudong Luo
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Editor information

Editors and Affiliations

  1. Faculty of Environment, Society and Design, Department of Applied Computing, Lincoln University, P.O. Box 84, 7647, Christchurch, New Zealand

    Patricia Anthony

  2. School of Information Science and Technology, University of Tokyo, 7-3-1, Hongo, 113-8656, Bunkyo-ku, Tokyo, Japan

    Mitsuru Ishizuka

  3. MIMOS Berhad, Knowledge Technology, Technology Park Malaysia,, 57000, Kuala Lumpur, Malaysia

    Dickson Lukose

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© 2012 Springer-Verlag Berlin Heidelberg

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Ma, W., Xiong, W., Luo, X. (2012). A D-S Theory Based AHP Decision Making Approach with Ambiguous Evaluations of Multiple Criteria. In: Anthony, P., Ishizuka, M., Lukose, D. (eds) PRICAI 2012: Trends in Artificial Intelligence. PRICAI 2012. Lecture Notes in Computer Science(), vol 7458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32695-0_28

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  • DOI: https://doi.org/10.1007/978-3-642-32695-0_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32694-3

  • Online ISBN: 978-3-642-32695-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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