Abstract
An optimization approach using a genetic algorithm in the search for global minima will be described. The method is based on the use of control variables to form the genotypes in each generation. This procedure allows an accurate representation of the control variables leading to a high resolution determination of the optimum solution. A set of genetic operators, appropriate for the operation on chromosomes represented by real numbers, is introduced. As an example, the method is used to obtain the lowest energy structures of rare gas microclusters, R n ( n = 4–10). Comparison of these results with published data shows an excellent agreement. It is shown that, in the present application, the genetic algorithm based method converges to the global minima much more rapidly than the simulated annealing approach. The role of the selection procedure used and the relative importance of the various operators will be discussed.
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