Optimization of molecular clusters configurations using a Genetic Algorithm

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We present a genetic algorithm developed (GA) to optimize molecular AF₆ cluster configurations with respect to their energy. The method is based on the Darvin's evolutionary theory: structures with lowest energies survive in a system of fixed number of clusters. Two existing structures from a given population are combined in a special way to produce a new structure (child) which is kept if its energy is lower than the highest energy in the ensemble. To keep the population constant we reject the structure with the highest energy. This algorithm gives a better result than the optimization techniques used previously. Using the GA we have found a new structure corresponding to the (seemingly) global minimum. The most important result is that the new structure is detected only if the molecular cluster contains more than a critical number of molecules.