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Proposal of a Realistic Many-Objective Test Suite

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Book cover Parallel Problem Solving from Nature – PPSN XVI (PPSN 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12269))

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Abstract

Real-world many-objective optimization problems are not always available as easy-to-use test problems. For example, their true Pareto fronts are usually unknown, and they are not scalable with respect to the number of objectives or decision variables. Thus, the performance of existing multi-objective evolutionary algorithms is always evaluated using artificial test problems. However, there exist some differences between frequently-used many-objective test problems and real-world problems. In this paper, first we clearly point out one difference with respect to the effect of changing the value of each decision variable on the location of the objective vector in the objective space. Next, to make artificial test problems more realistic, we introduce a coefficient matrix to their problem structure. Then, we demonstrate that a different coefficient matrix leads to a different difficulty of a test problem. Finally, based on these observations, we propose a realistic many-objective test suite using various coefficient matrices.

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Notes

  1. 1.

    The problem formulations of DTLZ7 and WFG7-9 are slightly different from the general structures mentioned in this paper. Due to the page limitation, the discussions in this paper do not include DTLZ7 and WFG7-9.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant No. 61876075), the Program for Guangdong Introducing Innovative and Enterpreneurial Teams (Grant No. 2017ZT07X386), Shenzhen Science and Technology Program (Grant No. KQTD2016112514355531), the Science and Technology Innovation Committee Foundation of Shenzhen (Grant No. ZDSYS2017-03031748284), the Program for University Key Laboratory of Guangdong Province (Grant No. 2017KSYS008).

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Authors and Affiliations

  1. Shenzhen Key Laboratory of Computational Intelligence,University Key Laboratory of Evolving Intelligent Systems of Guangdong Province, Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China

    Weiyu Chen, Hisao Ishibuchi & Ke Shang

Authors
  1. Weiyu Chen
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  2. Hisao Ishibuchi
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  3. Ke Shang
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Corresponding author

Correspondence to Hisao Ishibuchi .

Editor information

Editors and Affiliations

  1. Leiden University, Leiden, The Netherlands

    Thomas Bäck

  2. Leiden University, Leiden, The Netherlands

    Mike Preuss

  3. Leiden University, Leiden, The Netherlands

    André Deutz

  4. Sorbonne University, Paris, France

    Hao Wang

  5. Sorbonne University, Paris, France

    Carola Doerr

  6. Leiden University, Leiden, The Netherlands

    Michael Emmerich

  7. University of Münster, Münster, Germany

    Heike Trautmann

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Chen, W., Ishibuchi, H., Shang, K. (2020). Proposal of a Realistic Many-Objective Test Suite. In: Bäck, T., et al. Parallel Problem Solving from Nature – PPSN XVI. PPSN 2020. Lecture Notes in Computer Science(), vol 12269. Springer, Cham. https://doi.org/10.1007/978-3-030-58112-1_14

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  • DOI: https://doi.org/10.1007/978-3-030-58112-1_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58111-4

  • Online ISBN: 978-3-030-58112-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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