Approximate Quality Criteria for Difficult Multi-Objective Optimization Problems - Publikacja - MOST Wiedzy

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Approximate Quality Criteria for Difficult Multi-Objective Optimization Problems

Abstrakt

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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Zdzisław Kowalczuk, Tomasz Białaszewski. (2018). Approximate Quality Criteria for Difficult Multi-Objective Optimization Problems, 203-214. https://doi.org/10.1007/978-3-319-64474-5_17

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Licencja

Copyright (Springer International Publishing AG 2018)

Informacje szczegółowe

Kategoria:
Inna publikacyjna praca zbiorowa (w tym materiały konferencyjne)
Typ:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Tytuł wydania:
Advanced Solutions in Diagnostics and Fault Tolerant Control strony 203 - 214
ISSN:
2194-5357
Język:
angielski
Rok wydania:
2018
Opis bibliograficzny:
Kowalczuk Z., Białaszewski T.: Approximate Quality Criteria for Difficult Multi-Objective Optimization Problems// Advanced Solutions in Diagnostics and Fault Tolerant Control/ ed. J. Kacprzyk Cham (Switzerland): Springer International Publishing AG, 2018 , 2018, s.203-214

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