The problem of atomic structure optimization related to the minimization of its total energy is a fundamental physical problem as well as hard computational task. For the few last years we have presented some observations concerning the advantages and drawbacks of EA used as a tool to solve such questions. In this paper we would like to present some new approaches devoted to improve the general, not problem oriented part of algorithm. The results obtained for two techniques: population migration and Opposition-Based Learning show that the specific operators, designed for the given problem are still the most important part of algorithm.
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