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Solving Highly-Dimensional Multi-Objective Optimization Problems by Means of Genetic Gender

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Advanced and Intelligent Computations in Diagnosis and Control

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 386))

Abstract

Paper presents a computational optimization study using a genetic gender approach for solving multi-objective optimization problems of detection observers. In this methodology the information about an individual gender of all the considered solutions is applied for the purpose of making distinction between different groups of objectives. This information is drawn out of the fitness of individuals and applied during a current parental crossover in the performed evolutionary multi-objective optimization (EMO) processes.

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Authors and Affiliations

  1. Faculty of Electronics Telecommunication and Informatics, Gdańsk University of Technology, Narutowicza, 11/12, 80-233, Gdańsk, Poland

    Tomasz Białaszewski & Zdzisław Kowalczuk

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

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Editors and Affiliations

  1. Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Gdańsk, Poland

    Zdzisław Kowalczuk

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Białaszewski, T., Kowalczuk, Z. (2016). Solving Highly-Dimensional Multi-Objective Optimization Problems by Means of Genetic Gender. In: Kowalczuk, Z. (eds) Advanced and Intelligent Computations in Diagnosis and Control. Advances in Intelligent Systems and Computing, vol 386. Springer, Cham. https://doi.org/10.1007/978-3-319-23180-8_23

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  • DOI: https://doi.org/10.1007/978-3-319-23180-8_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23179-2

  • Online ISBN: 978-3-319-23180-8

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