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Visualizing the Pareto Frontier

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Multiobjective Optimization

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5252))

Abstract

We describe techniques for visualizing the Pareto optimal set that can be used if the multiobjective optimization problem considered has more than two objective functions. The techniques discussed can be applied in the framework of both MCDM and EMO approaches. First, lessons learned from methods developed for biobjective problems are considered. Then, visualization techniques for convex multiobjective optimization problems based on a polyhedral approximation of the Pareto optimal set are discussed. Finally, some visualization techniques are considered that use a pointwise approximation of the Pareto optimal set.

Reviewed by: Pekka Korhonen, Helsinki School of Economics, Finland; Sanaz Mostaghim, University of Karlsruhe, Germany; Roman Słowiński, Poznan University of Technology, Poland

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Authors and Affiliations

  1. Dorodnicyn Computing Centre of Russian Academy of Sciences, Vavilova str., 40, Moscow, 119333, Russia

    Alexander V. Lotov

  2. Department of Mathematical Information Technology, University of Jyväskylä, P.O. Box 35 (Agora), FI-40014, Finland

    Kaisa Miettinen

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  1. Alexander V. Lotov
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  2. Kaisa Miettinen
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Editor information

Editors and Affiliations

  1. Institute AIFB, University of Karlsruhe, Germany

    Jürgen Branke

  2. Department of Business Technology, Helsinki School of Economics, P.O. Box 1210, FI-00101, Helsinki, Finland

    Kalyanmoy Deb

  3. Department of Mathematical Information Technology, University of Jyväskylä, P.O. Box 35, (Agora), FI-40014, Finland

    Kaisa Miettinen

  4. Institute of Computing Science Poznan, University of Technology, 60-965, Poznan, Poland

    Roman Słowiński

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Lotov, A.V., Miettinen, K. (2008). Visualizing the Pareto Frontier. In: Branke, J., Deb, K., Miettinen, K., Słowiński, R. (eds) Multiobjective Optimization. Lecture Notes in Computer Science, vol 5252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88908-3_9

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  • DOI: https://doi.org/10.1007/978-3-540-88908-3_9

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