BMOO: a Bayesian Multi-Objective Optimization algorithm

Paul Feliot 1, 2, 3 Julien Bect 1, 2, 3 Emmanuel Vazquez 1, 2, 3
1 GdR MASCOT-NUM - Méthodes d'Analyse Stochastique des Codes et Traitements Numériques
2 L2S - Laboratoire des signaux et systèmes
3 IRT SystemX - IRT SystemX
Abstract : We address the problem of derivative-free multi-objective optimization of real-valued functions subject to multiple inequality constraints.
Keywords : Sequential Monte-Carlo Bayesian optimization Expected improvement Gaussian processes multi-objective optimization kriging Subset simulation
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Conference papers
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Submitted on : Friday, October 7, 2016 - 3:20:13 PM
Last modification on : Friday, December 20, 2019 - 11:48:04 AM
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CNRS | INSMI | TDS-MACS | L2S | SUP_LSS | CENTRALESUPELEC | SUP_SIGNAUX | IRT-SYSTEMX | UNIV-PARIS-SACLAY

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Paul Feliot, Julien Bect, Emmanuel Vazquez. BMOO: a Bayesian Multi-Objective Optimization algorithm. Journées annuelles du GdR MASCOT NUM (MASCOT NUM 2016), Mar 2016, Toulouse, France. ⟨hal-01377761⟩

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