In this paper, a one-dimensional MT inversion of the real-coded generalized genetic algorithm has been presented. By the initial grid of cross-species and integrated strategy, the phenomenon of premature convergence has been overcome and the efficiency of genetic optimization has been improved. Inversion and comparison results from theoretical model has shown that this algorithm is not dependent on the initial model and is not easy to a local minimum, and has the advantages of more multi-path probability searching and the implied parallel.