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- W2388894467 abstract "In order to deal with engineering design problem with computation-intensive black-box functions,a multi-objective optimization method based on the surrogate model guiding samples was proposed.Some Pareto solutions from the surrogate models built by adaptive extended radial basis functions were selected and added to the samples space for the next iteration.In that trend,the samples were more and more close to the Pareto solutions of actual problem.According to the distribution of the Pareto solutions obtained from the samples,it was considered as convergence condition.This method only uses the surrogate models to guide samples without validating the accuracy of surrogate models,and the obtained Pareto solutions are validated by the actual model.The current method shows the accuracy and effectiveness in the multi-objective testing function and is successfully applied in the optimization of variable binder force for sheet metal forming.Finally,it is believed that it has a great potential to be a practical tool for multi-objective optimization problem." @default.
- W2388894467 created "2016-06-24" @default.
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- W2388894467 date "2011-01-01" @default.
- W2388894467 modified "2023-09-24" @default.
- W2388894467 title "Multi-objective Optimization Method Based on Surrogate Model Guiding Sample" @default.
- W2388894467 hasPublicationYear "2011" @default.
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