A Particle Swarm Optimization based Neural Network and a Harmony Search Algorithm for Surface Roughness in Face Milling

In this paper, based on the acquired experimental data, the modeling of the face milling operation for surface roughness is performed by using an Improved Particle Swarm Optimization based Neural Network (IPSONN). Then, the Harmony search algorithm (HS) is utilized for optimizing the cutting parameters. The experimental evaluations of the obtained results using the optimal cutting parameters have shown the superiority of the proposed optimization approach.