In literature, heuristic algorithms have been successfully applied to a number of electromagnetic problems. The associated cost functions are commonly linked to full-wave analysis, leading to complexity and high computational expense. Arti-cial Neural Network is one of the most e®ective biological inspired techniques. In this article, an e±cient surrogate model is trained to replace the full-wave analysis in optimizing the bandwidth of microstrip antenna. The numerical comparison between ANN substitution model and full-wave characterization shows signi-cant improvements in time convergence and computational cost. To verify the robustness of this approach, all these concepts are integrated into a case study represented by a rectangular ring antenna with proximity-coupled feed antenna
