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Greedy Decremental Quick Hypervolume Subset Selection Algorithms

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Parallel Problem Solving from Nature – PPSN XVII (PPSN 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13399))

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Abstract

The contribution of this paper is fourfold. First, we present an updated implementation of the Improved Quick Hypervolume algorithm which is several times faster than the original implementation and according to the presented computational experiment it is at least competitive to other state-of-the-art codes for hypervolume computation. Second, we present a Greedy Decremental Lazy Quick Hypervolume Subset Selection algorithm. Third, we propose a modified Quick Hypervolume Extreme Contributor/Contribution algorithm using bounds from previous iterations of a greedy hypervolume subset selection algorithm. According to our experiments these two methods perform the best for greedy decremental hypervolume subset selection. Finally, we systematically compare performance of the fastest algorithms for greedy incremental and decremental hypervolume subset selection using two criteria: CPU time and the quality of the selected subset.

This research was funded by the Polish Ministry of Education and Science.

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Notes

  1. 1.

    All data sets used in this experiment, source code and the detailed results are available at https://chmura.put.poznan.pl/s/DxsmP72OS65Glce.

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Authors and Affiliations

  1. Faculty of Computing and Telecommunications, Poznan University of Technology, Piotrowo 3, 60-965, Poznan, Poland

    Andrzej Jaszkiewicz & Piotr Zielniewicz

Authors
  1. Andrzej Jaszkiewicz
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  2. Piotr Zielniewicz
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Correspondence to Piotr Zielniewicz .

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Editors and Affiliations

  1. TU Dortmund, Dortmund, Germany

    Günter Rudolph

  2. Leiden University, Leiden, The Netherlands

    Anna V. Kononova

  3. Shinshu University, Nagano, Japan

    Hernán Aguirre

  4. Technische Universität Dresden, Dresden, Germany

    Pascal Kerschke

  5. University of Stirling, Stirling, UK

    Gabriela Ochoa

  6. Jožef Stefan Institute, Ljubljana, Slovenia

    Tea Tušar

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Jaszkiewicz, A., Zielniewicz, P. (2022). Greedy Decremental Quick Hypervolume Subset Selection Algorithms. In: Rudolph, G., Kononova, A.V., Aguirre, H., Kerschke, P., Ochoa, G., Tušar, T. (eds) Parallel Problem Solving from Nature – PPSN XVII. PPSN 2022. Lecture Notes in Computer Science, vol 13399. Springer, Cham. https://doi.org/10.1007/978-3-031-14721-0_12

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  • DOI: https://doi.org/10.1007/978-3-031-14721-0_12

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