A Novel Subdivision-Based Optimal Design Algorithm for Multidimensional Electromagnetic Problems

For the large-scale electromagnetic problems, the existing optimization methods normally cannot search for a global optimal solution in the design space accurately and have a lower numerical efficiency. In order to mitigate these problems, this paper presents a novel optimal design algorithm based on the subdivision strategy. In the proposed algorithm, first, the whole design space is decomposed into a set number of subregions. Correspondingly, the problem is optimized simultaneously by applying any global optimizer to each subregion. The utilization of subregion strategy in the global optimizers can guarantee a faster convergence and a wider diversity of solutions. The implementation of parallel optimization will effectively reduce the expensive computational cost, especially for the design of the large-scale/multidimensional electromagnetic problems. Finally, the numerical efficiency and the searching ability of the proposed algorithm are validated through applications to two multidimensional electromagnetic problems. One is the design of a superconducting magnetic energy storage (SMES) system, and the other is the design of a Thomson-coil actuator used in the arc eliminator system.