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Upper trust bound feasibility criterion for mixed constrained Bayesian optimization with application to aircraft design

Priem, Rémy and Bartoli, Nathalie and Diouane, Youssef and Sgueglia, Alessandro Upper trust bound feasibility criterion for mixed constrained Bayesian optimization with application to aircraft design. (2020) Aerospace Science and Technology, 105. 1-24. ISSN 1270-9638

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Official URL: https://doi.org/10.1016/j.ast.2020.105980

Abstract

Bayesian optimization methods have been successfully applied to black box optimization problems that are expensive to evaluate. In this paper, we adapt the so-called super efficient global optimization algorithm to solve more accurately mixed constrained problems. The proposed approach handles constraints by means of upper trust bound, the latter encourages exploration of the feasible domain by combining the mean prediction and the associated uncertainty function given by the Gaussian processes. On top of that, a refinement procedure, based on a learning rate criterion, is introduced to enhance the exploitation and exploration trade-off. We show the good potential of the approach on a set of numerical experiments. Finally, we present an application to conceptual aircraft configuration upon which we show the superiority of the proposed approach compared to a set of the state-of-the-art black box optimization solvers.

Item Type:Article
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
French research institutions > Office National d'Etudes et Recherches Aérospatiales - ONERA (FRANCE)
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Deposited On:21 Jul 2020 08:44

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