A Hybird Method Based on Particle Swarm Optimization and Moth-Flame Optimization

This paper presents a novel hybrid optimization algorithm based on particle swarm optimization (PSO) and moth-flame optimization (MFO), called Hy-PSO-MFO, for solving the function optimization problems. In this algorithm, the ideas of PSO and MFO are integrated in a rational way to overcome the drawbacks of PSO and MFO, and thus improve the global search ability. The performance of the proposed algorithm is investigated on solving the well-known benchmark functions. The experimental results demonstrate that the Hy-PSO-MFO performs better than the standard PSO and original MFO in terms of solution quality and convergence speed.