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International Conference on Learning and Intelligent Optimization

LION 2014: Learning and Intelligent Optimization pp 121–136Cite as

Using Comparative Preference Statements in Hypervolume-Based Interactive Multiobjective Optimization

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8426))

Abstract

The objective functions in multiobjective optimization problems are often non-linear, noisy, or not available in a closed form and evolutionary multiobjective optimization (EMO) algorithms have been shown to be well applicable in this case. Here, our objective is to facilitate interactive decision making by saving function evaluations outside the “interesting” regions of the search space within a hypervolume-based EMO algorithm. We focus on a basic model where the Decision Maker (DM) is always asked to pick the most desirable solution among a set. In addition to the scenario where this solution is chosen directly, we present the alternative to specify preferences via a set of so-called comparative preference statements. Examples on standard test problems show the working principles, the competitiveness, and the drawbacks of the proposed algorithm in comparison with the recent iTDEA algorithm.

All authors have also been participating in the CNRS-Microsoft chair “Optimization for Sustainable Development (OSD)” at LIX, École Polytechnique, France.

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Notes

  1. 1.

    The source code is available at http://inrialix.gforge.inria.fr/interactive/.

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Author information

Authors and Affiliations

  1. INRIA Lille - Nord Europe, DOLPHIN Team, 59650, Villeneuve d’Ascq, France

    Dimo Brockhoff

  2. Microsoft Research, Cambridge, UK

    Youssef Hamadi

  3. Université Montpellier 2, LIRMM, UMR 5506 - CC477, 161 Rue Ada, 34095, Montpellier Cedex 5, France

    Souhila Kaci

Authors
  1. Dimo Brockhoff
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  2. Youssef Hamadi
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  3. Souhila Kaci
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Corresponding author

Correspondence to Dimo Brockhoff .

Editor information

Editors and Affiliations

  1. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

  2. AT&T Labs Research, Middletown, New Jersey, USA

    Mauricio G.C. Resende

  3. University of Florida, Gainesville, Florida, USA

    Chrysafis Vogiatzis

  4. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Jose L. Walteros

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Brockhoff, D., Hamadi, Y., Kaci, S. (2014). Using Comparative Preference Statements in Hypervolume-Based Interactive Multiobjective Optimization. In: Pardalos, P., Resende, M., Vogiatzis, C., Walteros, J. (eds) Learning and Intelligent Optimization. LION 2014. Lecture Notes in Computer Science(), vol 8426. Springer, Cham. https://doi.org/10.1007/978-3-319-09584-4_13

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  • DOI: https://doi.org/10.1007/978-3-319-09584-4_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09583-7

  • Online ISBN: 978-3-319-09584-4

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