An Optimization Approach for Emergency Relief Spectrum Resource Allocation Based on Genetic Algorithm and Simulated Annealing

Given the scarcity of spectrum resources and the complexity of the electromagnetic environment in emergency disaster relief scenarios, traditional spectrum allocation strategies often fail to meet practical requirements. This study proposes an optimization method that integrates Genetic Algorithm (GA), Simulated Annealing (SA), and Neural Network (NN). By leveraging NN to generate high-quality initial solutions and adaptively adjust mutation rates, combined with the global search capability of GA and the local optimization strength of SA, the proposed method significantly enhances spectrum allocation efficiency and anti-interference capability. The study provides an innovative and efficient solution for spectrum resource allocation in emergency disaster relief communication systems.