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Modified Covariance Matrix Adaptation – Evolution Strategy algorithm for constrained optimization under uncertainty, application to rocket design
International Journal for Simulation and Multidisciplinary Design Optimization
The design of complex systems often induces a constrained optimization problem under uncertainty. An adaptation of CMA-ES(k, l) 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.doi:10.1051/smdo/2015001 fatcat:lhnuc5s4qndohlbhg3lgbtn2em