Abstract: Genetic evolution strategy (GEs) was used in chemical clustering analysis.The clustering objective was formulated as a function of real-valued parameters.Combinatorial optimization usually encountered in clustering analysis, which is commonly time-consuming in computation, can be avoided, and therefore, the amount of computation can be significantly reduced.Global optimum might be achieved with the help of genetic algorithm.Results obtalned from four real chemical data sets substantiate the practicability of the method proposed in the paper.

Key words: Cluster analysis, Genetic evolution strategy, Hard clustering, Fuzzy clustering