Robust Covariance Matrix Adaptation Evolution Strategy: Optimal Design of Magnetic Devices Considering Material Variation

Uncertainties caused by material variation can significantly impair the characteristics of devices. Therefore, it is important to design devices whose performance not damaged even when variations occur. Robust optimization seeks for optimal solutions that are robust fluctuations due uncertainties variation, geometrical assembly tolerances, and changes in physical properties over time real-world problems. However, naive requires iterative calculations compute expected values, which need a huge computational burden. This paper introduces novel method magnetic using covariance matrix adaptation evolution strategy (CMA-ES). In this method, called RCMA-ES (robust CMA-ES), value objective function evaluated local average neighboring individuals without increasing computation cost. For validation, RCM-ES genetic algorithm (RGA), one methods load, was applied topology shield actuator, considering uncertainty BH characteristics. demonstrated be particularly more effective with large number dimensions compared RGA provides shapes insensitive