Quadrupole magnet design based on genetic multi-objective optimization

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.

Automated summary

This work proposes the optimization of a quadrupole magnet's geometry using a genetic algorithm. The algorithm, known as NSGA-III, is adapted to handle multi-objective optimization problems. The objectives of the optimization are to ensure high magnetic field quality and cost-efficiency in the magnet design. The results of a magnetostatic finite element model are used to compute the field quality and incorporated into the optimization algorithm. Extensive analysis is conducted on the optimization results, including studying Pareto front movements and identifying the best designs.