Abstract
In this paper we investigate the parallel version of the hierarchical chromosome based genetic algorithm (HCBGA) for finding the optimal initial mesh for self-adaptive hp-Finite Element Method (hp-FEM). The HCBGA algorithm solves the global optimization problem of r refinements in order to provide optimal starting mesh for the hp-FEM that will fit material data and singularities, and will result in the exponential convergence of the hp-FEM. The parallel algorithm is tested on the damaged Step-and-Flash Imprint Lithography problem, modeled by linear elasticity with thermal expansion coefficient.