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Minimum spanning tree (MST) problem is of high importance in network optimization, but it is also difficult for the traditional network optimization technique to deal with. In this paper, self-adaptive genetic algorithm (GA) approach is developed to deal with this problem. Without neglecting its network topology, the proposed method adopts the PruÂ¿fer number as the tree encoding and self-adaptation is used to enable strategy parameters to evolve along with the evolutionary process. Compared with the existing algorithm, the numerical analysis shows the efficiency and effectiveness of such self-adaptive GA approach on the MST problem.