Int. J. Simul. Multisci. Des. Optim.
Volume 6, 2015
|Number of page(s)||13|
|Published online||29 April 2015|
Modified Covariance Matrix Adaptation – Evolution Strategy algorithm for constrained optimization under uncertainty, application to rocket design
IFMA, EA3867, Laboratoires de Mécanique et Ingénieries, Clermont Université, CP 104488, 63000
2 Onera – The French Aerospace Lab, BP 80100, 91123 Palaiseau Cedex, France
3 CNES – Launchers Directorate, 52 rue Jacques Hillairet, 75612 Paris, France
* e-mail: email@example.com
Accepted: 3 March 2015
The design of complex systems often induces a constrained optimization problem under uncertainty. An adaptation of CMA-ES(λ, μ) optimization algorithm is proposed in order to efficiently handle the constraints in the presence of noise. The update mechanisms of the parametrized distribution used to generate the candidate solutions are modified. The constraint handling method allows to reduce the semi-principal axes of the probable research ellipsoid in the directions violating the constraints. The proposed approach is compared to existing approaches on three analytic optimization problems to highlight the efficiency and the robustness of the algorithm. The proposed method is used to design a two stage solid propulsion launch vehicle.
Key words: Evolutionary Strategy / Covariance Matrix Adaptation / CMA-ES / Uncertainty / Constrained optimization / Rocket design
© R. Chocat et al., Published by EDP Sciences, 2015
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.