Multi-Objective Optimization of Bi-Layer Metallic Sheet Using Pareto-Based Genetic Algorithm

The bi-layer materials have been used widely during past decades due to their specific characteristics like lighter weight, more corrosion resistance, and insulation features in comparison with mono-layers which consisting them. In this research the aim is achieving to best combination of bi-layer material (Al3105-St14) to satisfy two objectives of weight and formability while it has a constant total thickness. The represent the formability objective and is derived from M-K model associated with Barlat-Lian yield criteria. Another objective is weight of per unit area. The data of experiments are designed based on full factorial method and the surfaces are best polynomial which can fit the variables and objectives. The MATLAB software and the genetic algorithm (GA) are used to generate feasible combination of thickness to provide to minimize the weight and maximize the formability. The Pareto frontier is utilized to satisfy two objective functions simultaneously. The best answer is selected with norm approaching and minimum distance method.