Polychromatic Glow Optimization Algorithm (PGA)

Polychromatic Glow Optimization Algorithm (PGA)

This paper presents the Polychromatic Glow Optimization Algorithm (PGA), a novel physicsinspired metaheuristic that utilizes multi-wavelength luminosity to explore and exploit complex optimization landscapes. Drawing on analogies from interference, scattering, and color blending, PGA fosters both solution diversity and convergence speed by assigning spectral "glows" to candidate solutions and systematically guiding them toward optimal regions. Experimental evaluations on CEC2022 benchmarks confirm that PGA consistently outperforms or closely rivals state-of-the-art methods, exhibiting rapid convergence, low variance, and strong scalability.