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Interactive Robust Multiobjective Optimization Driven by Decision Rule Preference Model

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Book cover Modeling Decisions for Artificial Intelligence (MDAI 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5861))

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Abstract

Interactive procedures for MultiObjective Optimization (MOO) consist of a sequence of steps alternating calculation of a sample of non-dominated solutions and elicitation of preference information from the Decision Maker (DM). We consider three types of procedures, where in preference elicitation stage, the DM is just asked to indicate which solutions are relatively good in the proposed sample. In all three cases, the preference model is a set of “if . . . , then . . .” decision rules inferred from the preference information using the Dominance-based Rough Set Approach (DRSA) (3; 4; 11).

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References

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Author information

Authors and Affiliations

  1. Institute of Computing Science, Poznań University of Technology, Poznań

    Roman Słowiński

  2. Systems Research Institute, Polish Academy of Sciences, 00-441, Warsaw, Poland

    Roman Słowiński

Authors
  1. Roman Słowiński
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Editor information

Editors and Affiliations

  1. IIIA-CSIC, Campus UAB s/n, 08193, Bellaterra, Catalonia, Spain

    Vicenç Torra

  2. Toho Gakuen, 3-1-10 Naka, Kunitachi, 186-0004, Tokyo, Japan

    Yasuo Narukawa

  3. Graduate School of Engineering Science, Osaka University, 1-3, Machikaneyama, Toyonaka, 560-8531, Osaka, Japan

    Masahiro Inuiguchi

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© 2009 Springer-Verlag Berlin Heidelberg

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Słowiński, R. (2009). Interactive Robust Multiobjective Optimization Driven by Decision Rule Preference Model. In: Torra, V., Narukawa, Y., Inuiguchi, M. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2009. Lecture Notes in Computer Science(), vol 5861. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04820-3_1

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  • DOI: https://doi.org/10.1007/978-3-642-04820-3_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04819-7

  • Online ISBN: 978-3-642-04820-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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