Electromagnetic optimization design of a HTS magnet using the improved hybrid genetic algorithm Original Research Article

The genetic algorithm (GA) is an efficient method in the optimization of superconducting magnets, but there are some limitations of the GA applied to practice design of superconducting magnet, such as poor local search ability, premature convergence, etc. An improved hybrid genetic algorithm is developed by combination of the sequential quadratic programming (SQP). A high temperature superconducting (HTS) magnet by Bi-2223/Ag tape is designed through the improved hybrid GA. A new configuration of the HTS magnet which can reduce the winding volume and become more convenient to construct is suggested with consideration of the constraints, such as central magnetic filed, critical current characteristic, storage energy, and so on.