Abstract
This paper proposes a reliability-based design optimization approach to handle variability/uncertainties involved in the design variables/parameters of microwave absorber. The proposed approach uses hybrid genetic algorithm for optimization and Monte Carlo simulation with Latin hypercube sampling technique for probabilistic analysis to identify the optimal design of absorbing structure under probabilistic constraints. The proposed approach is illustrated with examples considering broadband absorbing coatings in the frequency range of 0.2–2, 2–8, and 0.5–8 GHz, respectively.