Discovery of new materials is essential in a lot if different fields, such as, space exploration, maritime industry and others. To stop new materials undergoing spontaneous reactions or reacting with the environment, they have to stable or at least metastable. That is where Global Geometry Optimization comes in, which tries to find global minimum on its Potential Energy Surface.
But modeling atoms is difficult as there is complex interplay of forces between each atom. A common simplification is to use the Lennard-Jones potential, which treats atoms as 3D points and models their interactions based on distance.
To find global minimum, Genetic Algorithm will be used and this research plans to study multiple different crossover strategies(sphere cut splice, uniform, two point, one point, arithmetical, plane cut splice crossover) and initialization strategies(box, sphere, octahedron initialization) to determine, which is the best for finding minimum for Lennard-Jones clusters. After analyzing results, it is inconclusive, which crossover produces best results, but it is clear that arithmetical produces worst results and octahedron initialization produces best results for clusters with size 10 to 15.