A simple hierarchical data structure (tree) and associated set of algorithms (written in Mathematica) have been developed that permit the direct manipulation of the topology of a molecule while simultaneously maintaining valid chemical valence. Coupled with a genetic algorithm optimization engine, these computational tools can be used to optimize chemical structures under the guidance of an appropriate fitness function. A detailed study of the factors that influence the performance of the method revealed that it is strongly dependent on the size and complexity of the evolved chemical structures. The effects of population size and choice of genetic operators are much smaller. The results of an exploration into the discovery of average molecular structures using this methodology is also described.
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