Fourier Transform Optimizer (FTO)

Fourier Transform Optimizer: A novel physics-inspired metaheuristic algorithm for optimization problems

This paper proposes a novel metaheuristic optimization algorithm, the Fourier Transform Optimizer (FTO), which integrates signal processing concepts with numerical analysis to enhance search performance. By operating in both the solution domain and frequency domain through the Discrete Fourier Transform (DFT), FTO applies frequency-based filtering to emphasize meaningful traits and suppress noise. It introduces innovative components such as differential frequency mixing, Lévy flight perturbations, orthogonal learning (OL), and Runge-Kutta (RK) strategies to maintain diversity, escape local optima, and accelerate convergence.