Bibliography

[And36]

R.F. Anderson. Determination of the Characteristics of Tapered Wings. NACA report. NACA, 1936. URL: https://ntrs.nasa.gov/citations/19930091647.

[AARDL23]

Amine Aziz-Alaoui, Olivier Roustant, and Matthias De Lozzo. A scalable problem to benchmark robust multidisciplinary design optimization techniques. working paper or preprint, February 2023. URL: https://hal.science/hal-04002825.

[BK97]

To Thanh Binh and Ulrich Korn. Mobes: a multiobjective evolution strategy for constrained optimization problems. In The third international conference on genetic algorithms (Mendel 97), volume 25, 27. 1997.

[BMartinez14]

Ernesto G Birgin and José Mario Martínez. Practical augmented Lagrangian methods for constrained optimization. SIAM, 2014.

[BILD12]

Christophe Blondeau, François-Xavier Irisarri, François-Henri Leroy, and Itham Salah El Din. A bi-level high fidelity aero-structural integrated design methodology. a focus on the structural sizing process. In Third Aircraft Structural Design Conference, Delft, The Netherlands. RAeS, October 2012. URL: https://www.researchgate.net/publication/259778547_A_Bi-Level_High_Fidelity_Aero-Structural_integrated_design_methodology_A_focus_on_the_structural_sizing_process.

[FF95]

Carlos M Fonseca and Peter J Fleming. An overview of evolutionary algorithms in multiobjective optimization. Evolutionary computation, 3(1):1–16, 1995.

[FSK08]

Alexander I. J. Forrester, Andras Sobester, and Andy J. Keane. Engineering design via surrogate modelling: a practical guide. Wiley, 2008.

[GBOG19]

F. Gallard, P.-J. Barjhoux, R. Olivanti, and A. Gazaix. GEMS, a Generic Engine for MDO Scenarios : Key Features In Application. In 2019 AIAA AVIATION Forum. 2019.

[GVGuenot+18]

François Gallard, Charlie Vanaret, Damien Guénot, Vincent Gachelin, Rémi Lafage, Benoit Pauwels, Pierre-Jean Barjhoux, and Anne Gazaix. Gems: a python library for automation of multidisciplinary design optimization process generation. In 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 0657. 2018.

[GGA+19]

Anne Gazaix, Francois Gallard, Vincent Ambert, Damien Guénot, Maxime Hamadi, Patrick Sarouille, Stéphane Grihon, Thierry Druot, Joel Brezillon, Thierry Lefebvre, Nathalie Bartoli, Remi Lafage, Vincent Gachelin, Justin Plakoo, Nicolas Desfachelles, Selime Gurol, Benoit Pauwels, and Charlie Vanaret. Industrial application of an advanced bi-level MDO formulation to an aircraft engine pylon optimization. In AIAA AVIATION Forum. American Institute of Aeronautics and Astronautics, 2019.

[GGG+17]

Anne Gazaix, François Gallard, Vincent Gachelin, Thierry Druot, Stéphane Grihon, Vincent Ambert, Damien Guénot, Rémi Lafage, Charlie Vanaret, Benoit Pauwels, and others. Towards the industrialization of new mdo methodologies and tools for aircraft design. In 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 3149. 2017.

[IH90]

T. Ishigami and T. Homma. An importance quantification technique in uncertainty analysis for computer models. In First International Symposium on Uncertainty Modeling and Analysis. 1990.

[KH15]

Graeme J Kennedy and Jason E Hicken. Improved constraint-aggregation methods. Computer Methods in Applied Mechanics and Engineering, 289:332–354, 2015.

[KSH01]

T. Kohonen, M. R. Schroeder, and T. S. Huang, editors. Self-Organizing Maps. Springer-Verlag New York, Inc., Secaucus, NJ, USA, 3rd edition, 2001. ISBN 3540679219.

[KS83]

Gerhard Kreisselmeier and Reinhold Steinhauser. Application of vector performance optimization to a robust control loop design for a fighter aircraft. International Journal of Control, 37(2):251–284, 1983.

[KJO+06]

Takayasu Kumano, Shinkyu Jeong, Shigeru Obayashi, Yasushi Ito, Keita Hatanaka, and Hiroyuki Morino. Multidisciplinary design optimization of wing shape for a small jet aircraft using kriging model. AIAA paper, 932:2006, 2006.

[LM12]

Andrew B. Lambe and Joaquim R. R. A. Martins. Extensions to the design structure matrix for the description of multidisciplinary design, analysis, and optimization processes. Structural and Multidisciplinary Optimization, 46:273–284, 2012. doi:10.1007/s00158-012-0763-y.

[ML13]

Joaquim R. R. A. Martins and Andrew B. Lambe. Multidisciplinary design optimization: a survey of architectures. AIAA Journal, 51:2049–2075, 2013. doi:10.2514/1.J051895.

[MM95]

Max D. Morris and Toby J. Mitchell. Exploratory designs for computational experiments. Journal of Statistical Planning and Inference, 1995.

[Niu88]

C. Niu. Airframe structural design: practical design information and data on aircraft structures. Conmilit Press, 1988.

[NW06]

J. Nocedal and S. J. Wright. Numerical Optimization. Springer, New York, 2nd edition, 2006.

[PAG96]

S. Padula, N. Alexandrov, and L. Green. MDO test suite at NASA Langley Research Center, chapter, pages. AIAA, 1996. URL: https://arc.aiaa.org/doi/abs/10.2514/6.1996-4028, doi:10.2514/6.1996-4028.

[PGOP00]

Carlo Poloni, Andrea Giurgevich, Luka Onesti, and Valentino Pediroda. Hybridization of a multi-objective genetic algorithm, a neural network and a classical optimizer for a complex design problem in fluid dynamics. Computer Methods in Applied Mechanics and Engineering, 186(2):403–420, 2000. URL: https://www.sciencedirect.com/science/article/pii/S0045782599003941, doi:https://doi.org/10.1016/S0045-7825(99)00394-1.

[Ray06]

Daniel P. Raymer. Aircraft Design: A Conceptual Approach (Education Series). AIAA (American Institute of Aeronautics & Ast), 2006. ISBN 1563478307.

[RSJ96]

Sellar RS, Batill SM, and Renaud JE. Response surface based, concurrent subspace optimization for multidisciplinary system design. AIAA paper, 714:1996, 1996.

[Shu07]

Pradyumn Kumar Shukla. On the normal boundary intersection method for generation of efficient front. In Computational Science–ICCS 2007: 7th International Conference, Beijing, China, May 27-30, 2007, Proceedings, Part I 7, 310–317. Springer, 2007.

[SSAJr98]

Jaroslaw Sobieszczanski-Sobieski, Jeremy S. Agte, and Robert R. Sandusky Jr. Bi-level integrated system synthesis (BLISS). Technical Report TM-1998-208715, NASA, Langley Research Center, 1998.

[Sva98]

Krister Svanberg. The method of moving asymptotes-modelling aspects and solution schemes. Lecture Notes for the DCAMM course Advanced Topics in Structural Optimization, 1998.

[TM06]

Nathan P. Tedford and Joaquim R. R. A. Martins. On the common structure of MDO problems: A comparison of architectures. In Proceedings of the 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Portsmouth, VA, September 2006. AIAA 2006-7080.

[TM10]

Nathan P. Tedford and Joaquim R.R.A. Martins. Benchmarking multidisciplinary design optimization algorithms. Optimization and Engineering, 11(1):159–183, February 2010. URL: http://dx.doi.org/10.1007/s11081-009-9082-6, doi:10.1007/s11081-009-9082-6.

[VGM17]

Charlie Vanaret, Francois Gallard, and Joaquim RRA Martins. On the consequences of the “no free lunch” theorem for optimization on the choice of an appropriate mdo architectures. In AIAA AVIATION Forum. AIAA, June 2017.

[VFM96]

R Viennet, Christian Fonteix, and Ivan Marc. Multicriteria optimization using a genetic algorithm for determining a pareto set. International Journal of Systems Science, 27(2):255–260, 1996.

[Wol96]

David H. Wolpert. The lack of a priori distinctions between learning algorithms. Neural computation, 8(7):1341–1390, 1996.