  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.
