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International Conference on Evolutionary Multi-Criterion Optimization

EMO 2017: Evolutionary Multi-Criterion Optimization pp 282–297Cite as

On Using Decision Maker Preferences with ParEGO

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10173))

Abstract

In this paper, an interactive version of the ParEGO algorithm is introduced for identifying most preferred solutions for computationally expensive multiobjective optimization problems. It enables a decision maker to guide the search with her preferences and change them in case new insight is gained about the feasibility of the preferences. At each interaction, the decision maker is shown a subset of non-dominated solutions and she is assumed to provide her preferences in the form of preferred ranges for each objective. Internally, the algorithm samples reference points within the hyperbox defined by the preferred ranges in the objective space and uses a DACE model to approximate an achievement (scalarizing) function as a single objective to scalarize the problem. The resulting solution is then evaluated with the real objective functions and used to improve the DACE model in further iterations. The potential of the proposed algorithm is illustrated via a four-objective optimization problem related to water management with promising results.

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Acknowledgment

This work was supported by the FiDiPro project DeCoMo funded by TEKES, The Finnish Funding Agency for Innovation. The authors want to thank Mr. Tinkle Chugh, Prof. Yaochu Jin, Prof. Kaisa Miettinen, and Dr. Karthik Sindhya for discussions related to the ideas presented in the paper. In addition, the authors would like to acknowledge Prof. Patrick Reed’s group Decision Analytics for Complex Systems (Cornell University) related to their parallel coordinate plotting tool.

Author information

Authors and Affiliations

  1. Faculty of Information Technology, University of Jyvaskyla, P.O. Box 35 (Agora), FI-40014, University of Jyvaskyla, Finland

    Jussi Hakanen

  2. School of Computer Science, University of Birmingham, Edgbaston B15 2TT, Birmingham, UK

    Joshua D. Knowles

Authors
  1. Jussi Hakanen
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  2. Joshua D. Knowles
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Corresponding author

Correspondence to Jussi Hakanen .

Editor information

Editors and Affiliations

  1. University of Münster, Münster, Germany

    Heike Trautmann

  2. TU Dortmund University, Dortmund, Germany

    Günter Rudolph

  3. University of Wuppertal, Wuppertal, Germany

    Kathrin Klamroth

  4. CINVESTAV-IPN, Mexico City, Mexico

    Oliver Schütze

  5. Clemson University, Clemson, South Carolina, USA

    Margaret Wiecek

  6. University of Surrey, Guildford, United Kingdom

    Yaochu Jin

  7. University of Münster, Münster, Germany

    Christian Grimme

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Hakanen, J., Knowles, J.D. (2017). On Using Decision Maker Preferences with ParEGO. In: Trautmann, H., et al. Evolutionary Multi-Criterion Optimization. EMO 2017. Lecture Notes in Computer Science(), vol 10173. Springer, Cham. https://doi.org/10.1007/978-3-319-54157-0_20

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  • DOI: https://doi.org/10.1007/978-3-319-54157-0_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54156-3

  • Online ISBN: 978-3-319-54157-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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