Multi-objective Minimum Spanning Tree Algorithms Based on Genetic Algorithms

Solve the problem of minimum spanning tree.The traditional algorithm for solving multi-objective minimum spanning tree problem is of high computational complexity,and difficult to obtain satisfactory solutions.Based on graph theory and genetic algorithm,a improved genetic algorithm was proposed based on multi-objective minimum spanning tree methods.The algorithm used binary code to express minimum trees,and then used depth-first search algorithm to determine the connectivity of the graph.A new fitness function was given to improve the algorithm execution speed and evolutionary efficiency.The simulation results show that compared with the classical Prim algorithm and Kruskal algorithm,the new algorithm is of low complexity,can obtain the minimum spanning tree in the first genetic evolution process,and is suitable for solving different types of problems of multi-objective minimum trees.