Variable Neighborhood Search for Robust Optimization and Applications to Aerodynamics

Abstract : Many real-life applications lead to the definition of robust optimization problems where the objective function is a black box. This may be due, for example, to the fact that the objective function is evaluated through computer simulations, and that some parameters are uncertain. When this is the case, existing algorithms for optimization are not able to provide good-quality solutions in general. We propose a heuristic algorithm for solving black box robust optimization problems based on the minimax formulation of the problem.We also apply this algorithm for the solution of a wing shape optimization where the objective function is a computationally expensive black box. Preliminary computational experiments are reported.
Type de document :
Communication dans un congrès
8th International Conference on Large-Scale Scientific Computations (LSSC11), 2012, Sozopol, Bulgaria. Springer, 7116, pp.230-237, 2012, Lecture Notes in Computer Science
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https://hal.inria.fr/hal-00756948
Contributeur : Antonio Mucherino <>
Soumis le : samedi 24 novembre 2012 - 13:54:21
Dernière modification le : mercredi 16 mai 2018 - 11:23:35

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  • HAL Id : hal-00756948, version 1

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Antonio Mucherino, Fuchs Martin, Gratton Serge, Vasseur Xavier. Variable Neighborhood Search for Robust Optimization and Applications to Aerodynamics. 8th International Conference on Large-Scale Scientific Computations (LSSC11), 2012, Sozopol, Bulgaria. Springer, 7116, pp.230-237, 2012, Lecture Notes in Computer Science. 〈hal-00756948〉

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