The multiobjective optimization of an eight‐block actively‐shielded solenoid has been performed. After a study of each objective function for simplified configurations, up to three objectives in mutual contrast and 16 design variables have been considered for the full model. In order to obtain a set of equivalent optimal solutions, an evolution strategy of lowest order with a multistart grid has been linked to a Pareto sorting algorithm. Sparsity in both design and objective space and the improvement of all objectives is a feature of the solutions belonging to the Pareto optimal set.
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Paolo Di Barba (2002) studied this question.
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