Pareto-optimal analysis of Zn-coated Fe in the presence of dislocations using genetic algorithms

To design a coating that will absorb maximum energy prior to failure with minimum deformation, the shearing process of polycrystalline Zn coated Fe is simulated in the presence of dislocations, using molecular dynamics. The results fed to an Evolutionary Neural Network generated the meta-models of objective functions required in the subsequent Pareto-optimization task using a Multi-objective Genetic Algorithm. Similar calculations conducted for single crystals, and also in the absence of dislocations, are compared and analyzed.