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C. FERREIRA In H. J. Caulfield, S.-H. Chen, H.-D. Cheng, R. Duro, V. Honavar, E. E. Kerre, M. Lu, M. G. Romay, T. K. Shih, D. Ventura, P. P. Wang, Y. Yang, eds., Proceedings of the 6th Joint Conference on Information Sciences, 4th International Workshop on Frontiers in Evolutionary Algorithms, pages 614-617, Research Triangle Park, North Carolina, USA, 2002. Mutation, Transposition, and Recombination: An Analysis of the Evolutionary Dynamics Abstract   Gene expression programming (GEP) uses mutation, transposition, and crossover to create variation. Although there exists a large body of work in genetic algorithms concerning the roles of mutation and recombination, these results not only do not apply to GEP due to the genotype/phenotype representation but also seem to contradict the GEP experience. Therefore, and given the diversity of GEP operators, it is convenient to develop some kind of understanding of their power. The aim of this work is to help develop such an understanding and to show the evolutionary dynamics and the transforming power of each genetic operator, with their advantages and limitations. Home | Contents | Next