genetic algorithms;  Minimal spanning tree;  evolutionary strategies;  Network optimization

Based on graph theory and genetic algorithm, an improved genetic algorithm for finding the minimum spanning tree is proposed. The algorithm uses binary coding to represent the minimum tree problem, uses the depth-first search algorithm to judge the connectivity of the graph, and designs the corresponding fitness function, one-parent transposition operator and single-parent reversal operator, as well as four control evolution strategies to improve the execution speed and evolutionary efficiency of the algorithm. Compared with the Kruskal algorithm, the algorithm can obtain a batch of minimum spanning trees in a single genetic evolution process, which is suitable for solving different types of minimum tree problems.