A Novel Subregion-Based Multidimensional Optimization of Electromagnetic Devices Assisted by Kriging Surrogate Model

作者：Xia, Bin; Ren, Ziyan; Choi, Kyung; Koh, Chang-Seop^*

来源：IEEE Transactions on Magnetics, 2017, 53(6): 9401204.

DOI：10.1109/TMAG.2017.2655099

• Computing cost
• Kriging
• particle swarm optimization (PSO) algorithm
• subregion

A novel subregion-based optimization strategy utilizing an adaptive dynamic Taylor Kriging (ADTK) surrogate model is developed for a multidimensional optimal design of electromagnetic devices. In the algorithm, the whole design space is divided into a series of subregion, which has its own local ADTK model with optimal set of basis functions. For all subregions, a global optimal solution is found by using particle swarm optimization with the help of the local ADTK models of the objective and constraint functions. The proposed algorithm improves remarkably the accuracy of the ADTK model by reducing the computational complexity. It also significantly reduces the computational cost especially for an optimal design of large-scale multidimensional problems. Finally, the effectiveness of the proposed method is demonstrated through applications to two benchmark problems: TEAM problems 22 and 25.

• 出版日期2017-6
• 单位沈阳工业大学