A New Hybrid Algorithm Based on PSO and Fireworks Algorithm for Optimal Design of Metasurface Absorber in RF Energy Harvesting

Abstract

To address the nonlinear, multimodal, and computationally intensive challenges inherent in the optimal design of metasurface absorbers for radio frequency (RF) energy harvesting, we propose an innovative hybrid algorithm that combines particle swarm optimization (PSO) and fireworks algorithm (FWA). The proposed hybrid algorithm features several enhancements: 1) a quasi-scaling (Q.S.) mechanism, inspired by the frequency response of electromagnetic (EM) devices shifting with the scaling of physical parameters, is developed to balance the exploration and exploitation searches; 2) a self-adaptive inertia weight is introduced to enhance the convergence speed; and 3) an elite-preservation strategy is employed to ensure a global convergence. The effectiveness and merits of the proposed algorithm are validated by solving first mathematical test functions; then, two practical cases: a multi-band absorber (1.8–3 GHz, 5.85 GHz) and a broadband absorber (8–15 GHz), where a new dual-polarized metasurface absorber topology is employed. Both cases are efficiently optimized, demonstrating high absorption efficiencies within the targeted bands, and validated by both simulated and measured results.