A Surrogate Genetic Programming Based Model to Facilitate Robust Multi-Objective Optimization: A Case Study in Magnetostatics

@article{Mendes2013ASG,
  title={A Surrogate Genetic Programming Based Model to Facilitate Robust Multi-Objective Optimization: A Case Study in Magnetostatics},
  author={Marcus Henrique Soares Mendes and Gustavo Lu{\'i}s Soares and Jean-Louis Coulomb and Jo{\~a}o A. Vasconcelos},
  journal={IEEE Transactions on Magnetics},
  year={2013},
  volume={49},
  pages={2065-2068}
}
A common drawback of robust optimization methods is the effort expended to compute the influence of uncertainties, because the objective and constraint functions must be re-evaluated many times. This disadvantage can be aggravated if time-consuming methods, such as boundary or finite element methods are required to calculate the optimization functions. To overcome this difficulty, we propose the use of genetic programming to obtain high-quality surrogate functions that are quickly evaluated… CONTINUE READING

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