Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Rodolphe Le Riche"'
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 7916 (2024)
This paper introduces an evolutionary algorithm for objective functions defined over clouds of points of varying sizes. Such design variables are modeled as uniform discrete measures with finite support and the crossover and mutation operators of the
Externí odkaz:
https://doaj.org/article/3fcf466d2b0a4cf9be9de5137066041c
Autor:
Jhouben Cuesta Ramirez, Rodolphe Le Riche, Olivier Roustant, Guillaume Perrin, Cédric Durantin, Alain Glière
Publikováno v:
Advanced Modeling and Simulation in Engineering Sciences, Vol 9, Iss 1, Pp 1-29 (2022)
Abstract Most real optimization problems are defined over a mixed search space where the variables are both discrete and continuous. In engineering applications, the objective function is typically calculated with a numerically costly black-box simul
Externí odkaz:
https://doaj.org/article/b30aba4e600049089d0c50cb307b110d
Publikováno v:
Croatian Operational Research Review, Vol 9, Iss 1, Pp 1-10 (2018)
The need for globally optimizing expensive-to-evaluate functions frequently occurs in many real-world applications. Among the methods developed for solving such problems, the Efficient Global Optimization (EGO) is regarded as one of the state-of-the-
Externí odkaz:
https://doaj.org/article/ca32864d20fd42839a38b68f5a88f591
Autor:
Jhouben Cuesta Ramirez, Rodolphe Le Riche, Olivier Roustant, Guillaume Perrin, Cédric Durantin, Alain Glière
Publikováno v:
Advanced Modeling and Simulation in Engineering Sciences
Advanced Modeling and Simulation in Engineering Sciences, 2022, ⟨10.21203/rs.3.rs-1050987/v1⟩
Advanced Modeling and Simulation in Engineering Sciences, 2022, ⟨10.21203/rs.3.rs-1050987/v1⟩
Most real optimization problems are defined over a mixed search space where the variables are both discrete and continuous. In engineering applications, the objective function is typically calculated with a numerically costly black-box simulation.Gen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b78d9c8a9bf6ff1eb6ce1868d215934c
https://hal-emse.ccsd.cnrs.fr/emse-03413829
https://hal-emse.ccsd.cnrs.fr/emse-03413829
Autor:
Victor Picheny, Rodolphe Le Riche
Publikováno v:
Structural and Multidisciplinary Optimization
Structural and Multidisciplinary Optimization, 2021, ⟨10.1007/s00158-021-02977-1⟩
Structural and Multidisciplinary Optimization, Springer Verlag (Germany), 2021, ⟨10.1007/s00158-021-02977-1⟩
Structural and Multidisciplinary Optimization, 2021, ⟨10.1007/s00158-021-02977-1⟩
Structural and Multidisciplinary Optimization, Springer Verlag (Germany), 2021, ⟨10.1007/s00158-021-02977-1⟩
International audience; It is commonly believed that Bayesian optimization (BO) algorithms are highly efficient for optimizing numerically costly functions. However, BO is not often compared to widely different alternatives, and is mostly tested on n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32b45fb6a47ce1ef8147d4148bd0e248
https://hal.science/hal-03188590
https://hal.science/hal-03188590
Publikováno v:
Structural and Multidisciplinary Optimization
Structural and Multidisciplinary Optimization, 2020, 61, pp.2343-2361. ⟨10.1007/s00158-019-02458-6⟩
Structural and Multidisciplinary Optimization, Springer Verlag (Germany), 2020, 61, pp.2343-2361. ⟨10.1007/s00158-019-02458-6⟩
Structural and Multidisciplinary Optimization, Springer Verlag (Germany), 2019
Structural and Multidisciplinary Optimization, 2020, 61, pp.2343-2361. ⟨10.1007/s00158-019-02458-6⟩
Structural and Multidisciplinary Optimization, Springer Verlag (Germany), 2020, 61, pp.2343-2361. ⟨10.1007/s00158-019-02458-6⟩
Structural and Multidisciplinary Optimization, Springer Verlag (Germany), 2019
International audience; Parametric shape optimization aims at minimizing an objective function f(x) where x are CAD parameters. This task is difficult when f is the output of an expensive-to-evaluate numerical simulator and the number of CAD paramete
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39c163582fc96512046dbe45460f0420
https://hal-emse.ccsd.cnrs.fr/emse-02390627
https://hal-emse.ccsd.cnrs.fr/emse-02390627
Publikováno v:
Aerospace System Analysis and Optimization in Uncertainty
Loic Brevault; Mathieu Balesdent; Jerome Morio. Aerospace System Analysis and Optimization in Uncertainty, 156, Springer, pp.295-320, 2020, Springer Optimization and its Applications, 978-3-03 0-39126-3. ⟨10.1007/978-3-030-39126-3_8⟩
Springer Optimization and Its Applications ISBN: 9783030391256
Loic Brevault; Mathieu Balesdent; Jerome Morio. Aerospace System Analysis and Optimization in Uncertainty, 156, Springer, pp.295-320, 2020, Springer Optimization and its Applications, 978-3-03 0-39126-3. ⟨10.1007/978-3-030-39126-3_8⟩
Springer Optimization and Its Applications ISBN: 9783030391256
International audience; Multi-fidelity models aim at combining models of different fidelities to achieve the desired accuracy at a lower computational cost. In Section 8.2, the connection between MDO, multi-fidelity and cokriging is made through a re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8815ffdfd1100affb0d455caf0c8b8e2
https://hal.science/hal-02444005/document
https://hal.science/hal-02444005/document
Autor:
Hilaire Drouineau, Dimo Brockhoff, Victor Picheny, Stéphanie Mahévas, Lauriane Rouan, Rodolphe Le Riche, Patrick Lambert, Robert Faivre, Sigrid Lehuta, Nicolas Dumoulin, Christophe Soulié
pdf available at https://www.preprints.org/manuscript/201912.0249/v1; Calibrating ecological models or making decisions with them is an optimisation problem with challenging methodological issues. Depending on the optimisation formulation, there may
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d167bb76d7e8d0a39d796c3437ab2f65
https://hal.inria.fr/hal-02418667
https://hal.inria.fr/hal-02418667
Publikováno v:
Archives of Computational Methods in Engineering
Archives of Computational Methods in Engineering, Springer Verlag, 2019, 26 (1), pp.61-106. ⟨10.1007/s11831-017-9226-3⟩
Archives of Computational Methods in Engineering, 2019, 26 (1), pp.61-106. ⟨10.1007/s11831-017-9226-3⟩
Archives of Computational Methods in Engineering, Springer Verlag, 2019, 26 (1), pp.61-106. ⟨10.1007/s11831-017-9226-3⟩
Archives of Computational Methods in Engineering, 2019, 26 (1), pp.61-106. ⟨10.1007/s11831-017-9226-3⟩
International audience; Metamodeling, the science of modeling functions observed at a finite number of points, benefits from all auxiliary information it can account for. Function gradients are a common auxiliary information and are useful for predic
Publikováno v:
Annals of Mathematics and Artificial Intelligence
Annals of Mathematics and Artificial Intelligence, 2019, pp 1-26. ⟨10.1007/s10472-019-09644-8⟩
Annals of Mathematics and Artificial Intelligence, Springer Verlag, 2019, pp 1-26. ⟨10.1007/s10472-019-09644-8⟩
Annals of Mathematics and Artificial Intelligence, 2019, pp 1-26. ⟨10.1007/s10472-019-09644-8⟩
Annals of Mathematics and Artificial Intelligence, Springer Verlag, 2019, pp 1-26. ⟨10.1007/s10472-019-09644-8⟩
International audience; Multi-objective optimization aims at finding trade-off solutions to conflicting objectives. These constitute the Pareto optimal set. In the context of expensive-to-evaluate functions, it is impossible and often non-informative
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8dc62abed72f59a83c95fd4b495ba66
https://hal-emse.ccsd.cnrs.fr/emse-01957614
https://hal-emse.ccsd.cnrs.fr/emse-01957614