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Approximate Quality Criteria for Difficult Multi-Objective Optimization Problems

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Advanced Solutions in Diagnostics and Fault Tolerant Control (DPS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 635))

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Abstract

This paper introduces approximate analytic quality criteria useful in assessing the efficiency of evolutionary multi-objective optimization (EMO) procedures. We present a summary of extensive research into computing. In the performed comparative study we take into account the various approaches of the state-of-the-art, in order to objectively assess the EMO performance in highly dimensional spaces; where some executive criteria, such as those based on the true Pareto front, are difficult to calculate. Whereas, on the other hand, the proposed approximated quality criteria are easy to implement, computationally inexpensive, and sufficiently effective.

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Authors and Affiliations

  1. Department of Robotics and Decision Systems, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk, Poland

    Zdzisław Kowalczuk & Tomasz Białaszewski

Authors
  1. Zdzisław Kowalczuk
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  2. Tomasz Białaszewski
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Correspondence to Tomasz Białaszewski .

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Editors and Affiliations

  1. Faculty of Mechatronics, Institute of Automatic Control and Robotics, Warsaw University of Technology, Warsaw, Poland

    Jan M. Kościelny

  2. Faculty of Mechatronics, Institute of Automatic Control and Robotics, Warsaw University of Technology, Warsaw, Poland

    Michał Syfert

  3. Faculty of Mechatronics, Institute of Automatic Control and Robotics, Warsaw University of Technology, Warsaw, Poland

    Anna Sztyber

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Kowalczuk, Z., Białaszewski, T. (2018). Approximate Quality Criteria for Difficult Multi-Objective Optimization Problems. In: Kościelny, J., Syfert, M., Sztyber, A. (eds) Advanced Solutions in Diagnostics and Fault Tolerant Control. DPS 2017. Advances in Intelligent Systems and Computing, vol 635. Springer, Cham. https://doi.org/10.1007/978-3-319-64474-5_17

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  • DOI: https://doi.org/10.1007/978-3-319-64474-5_17

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  • Online ISBN: 978-3-319-64474-5

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