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The growth of evolutionary computing (EC) methods in the exploration ofcomplex potential energy landscapes of atomic and molecular clusters, as wellas crystals over the last decade or so is reviewed. The trend of growthindicates that pure as well as hybrid evolutionary computing techniques inconjunction of DFT has been emerging as a powerful tool, although work onmolecular clusters has been rather limited so far. Some attempts to solve theatomic/molecular Schrodinger Equation (SE) directly by genetic algorithms (GA)are available in literature. At the Born-Oppenheimer level of approximationGA-density methods appear to be a viable tool which could be more extensivelyexplored in the coming years, specially in the context of designing moleculesand materials with targeted properties.

Pure and Hybrid Evolutionary Computing in Global Optimization of Chemical Structures: from Atoms and Molecules to Clusters and Crystals