The Artificial Hummingbird Algorithm (AHA) is a bio-inspired optimization algorithm that simulates hummingbird foraging behavior.[1] The present study recommends a hybrid approach combining AHA with PSO algorithms for its improved convergence speed and solution quality. Experimentation shows the hybrid AHA performing better than the single AHA and other algorithms with better solution quality and stability for challenging problems of optimization[2]. In this paper author to optimize for enhanced convergence and accuracy in algorithm Artificial Hummingbird Algorithm with Particle Swarm Optimization.