Improved multi-objective ant colony algorithm for multi-objective minimum spanning tree
求解多目标最小生成树的改进多目标蚁群算法

Multi-objective minimum spanning tree problem is a typical NP problem. For this problem, this paper proposed an improved ant colony algorithm for multi-objective, non-inferiority in order to obtain a better front end, by choosing the number of pheromone diffusion source and diffusion strategy avoid premature convergence. And the introduction of mutation operator was to enhance population diversity and avoid falling into local optimal solution algorithm prematurely. Comparison of experimental results shows that for multi-objective minimum spanning tree problem, the algorithm is effective not only in the solution efficiency of the quality of reconciliation is better than related algorithms. With the expansion of scale of the problem and algorithm remains a good performance.