This work suggests to optimize the geometry of a quadrupole magnet by means of a genetic algorithm adapted to solve multi-objective optimization problems. To that end, a non-domination sorting genetic algorithm known as NSGA-III is used. The optimization objectives are chosen such that a high magnetic field quality in the aperture of the magnet is guaranteed, while simultaneously the magnet design remains cost-efficient. The field quality is computed using a magnetostatic finite element model of the quadrupole, the results of which are post-processed and integrated into the optimization algorithm. An extensive analysis of the optimization results is performed, including Pareto front movements and identification of best designs.

翻译：本研究提出采用适用于求解多目标优化问题的遗传算法对四极磁体几何结构进行优化。为此，采用非支配排序遗传算法NSGA-III作为优化工具。优化目标的选取兼顾两方面：确保磁体孔径内具有高磁场品质，同时保持磁体设计的成本效益。磁场品质通过四极磁体的静磁场有限元模型进行计算，计算结果经后处理后集成至优化算法中。对优化结果进行了全面分析，包括帕累托前沿演变及最优设计方案的识别。