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International Conference on Intelligent Computing

ICIC 2017: Intelligent Computing Theories and Application pp 14–25Cite as

A Fast Approximate Hypervolume Calculation Method by a Novel Decomposition Strategy

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10361))

Abstract

In this paper, we present a new method to fast approximate the hypervolume measurement by improving the classical Monte Carlo sampling method. Hypervolume value can be used as a quality indicator or selection indicator for multiobjective evolutionary algorithms (MOEAs), and thus the efficiency of calculating this measurement is of crucial importance especially in the case of large sets or many dimensional objective spaces. To fast calculate hypervolume, we develop a new Monte Carlo sampling method by decreasing the amount of Monte Carlo sample points using a novel decomposition strategy in this paper. We first analyze the complexity of the proposed algorithm in theory, and then execute a series experiments to further test its efficiency. Both simulation experiments and theoretical analysis verify the effectiveness and efficiency of the proposed method.

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Acknowledgment

This work was supported in part by the National Natural Science Foundation of China under Grant 61673121, in part by the Projects of Science and Technology of Guangzhou under Grant 201508010008, and in part by the China Scholarship Council.

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Authors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Weisen Tang, Hailin Liu & Lei Chen

Authors
  1. Weisen Tang
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  2. Hailin Liu
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  3. Lei Chen
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Corresponding author

Correspondence to Hailin Liu .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Politecnico di Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong, North Wollongong, New South Wales, Australia

    Prashan Premaratne

  4. Indian Institute of Technology, Kanpur, India

    Phalguni Gupta

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Tang, W., Liu, H., Chen, L. (2017). A Fast Approximate Hypervolume Calculation Method by a Novel Decomposition Strategy. In: Huang, DS., Bevilacqua, V., Premaratne, P., Gupta, P. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science(), vol 10361. Springer, Cham. https://doi.org/10.1007/978-3-319-63309-1_2

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  • DOI: https://doi.org/10.1007/978-3-319-63309-1_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63308-4

  • Online ISBN: 978-3-319-63309-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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