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On the Impact of Covariance Functions in Multi-Objective Bayesian Optimization for Engineering Design

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F20%3A73598638" target="_blank" >RIV/61989592:15310/20:73598638 - isvavai.cz</a>

  • Result on the web

    <a href="https://obd.upol.cz/id_publ/333178524" target="_blank" >https://obd.upol.cz/id_publ/333178524</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.2514/6.2020-1867" target="_blank" >10.2514/6.2020-1867</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    On the Impact of Covariance Functions in Multi-Objective Bayesian Optimization for Engineering Design

  • Original language description

    Multi-objective Bayesian optimization (BO) is a highly useful class of methods that can effectively solve computationally expensive engineering design optimization problems with multiple objectives. However, the impact of covariance function, which is an important part of multi-objective BO, is rarely studied in the context of engineering optimization. We aim to shed light on this issue by performing numerical experiments on engineering design optimization problems, primarily low-fidelity problems so that we are able to statistically evaluate the performance of BO methods with various covariance functions. In this paper, we performed the study using a set of subsonic airfoil optimization cases as benchmark problems. Expected hypervolume improvement was used as the acquisition function to enrich the experimental design. Results show that the choice of the covariance function give a notable impact on the performance of multi-objective BO. In this regard, Kriging models with Matern-3/2 is the most robust method in terms of the diversity and convergence to the Pareto front that can handle problems with various complexities.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10102 - Applied mathematics

Result continuities

  • Project

    <a href="/en/project/EF17_049%2F0008408" target="_blank" >EF17_049/0008408: Hydrodynamic design of pumps</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    AIAA Scitech 2020 Forum

  • ISBN

    978-1-62410-595-1

  • ISSN

  • e-ISSN

  • Number of pages

    13

  • Pages from-to

    1-13

  • Publisher name

    American Institute of Aeronautics and Astronautics, Inc.

  • Place of publication

    Orlando, FL

  • Event location

    Orlando, FL, USA

  • Event date

    Jan 6, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article