The application of imperialist competitive algorithm for optimization of deposition rate in submerged arc welding process using TiO2 nano particle

Abstract

We used a novel optimization algorithm based on the imperialist competitive algorithm (ICA) to optimize the deposition rate in the submerged arc welding (SAW) process. This algorithm offers some advantages such as simplicity, accuracy and time saving. Experiments were conducted based on a five factor, five level rotatable central composite design (RCCD) to collect welding data for deposition rate as a function of welding current, arc voltage, contact tip to plate distance, welding speed and thickness of TiO2 nanoparticles coated on the plates of mild steel. Furthermore, regression equation for deposition rate was obtained using least squares method. The regression equation as the cost function was optimized using ICA. Ultimately, the levels of input variables to achieve maximum deposition rate were obtained using ICA. Computational results indicate that the proposed algorithm is quite effective and powerful in optimizing the cost function.