Fast Optimization of Microwave Filters using Surrogate-Based Optimization Methods

Abstract — This paper investigates the use of surrogate-based optimization to optimize the behav-ioral response of broadband microwave filters. The proposed method makes use of an efficient infill cri-terion (called expected improvement) that sequen-tially samples the response of the device at well-chosen regions in the design space. Based on these data samples, successive global surrogate models are built that become increasingly accurate near the optimum solution. A microwave filter exam-ple confirms that this approach significantly acceler-ates device optimization when compared to standard gradient-based methods.