The role of local optimizations in evolutionary process of atomic clusters modeling

The application of genetic algorithms in a physical problem of modeling of isolated atomic clusters is the topic of our research. Evolutionary algorithms are a mechanism of the global optimization learning about the solution of the search space. This mechanism plays the role of giving the candidates to global optima. We can use the local optimization in the evolutionary process to improve the efficiency of our algorithm. The goal of our work is evaluation of the influence of the local optimization methods (type of simple gradient) on the growing of the efficiency and accuracy of the evolutionary process in optimization of atomic clusters modeling.