求解多目标最小生成树的改进多目标蚁群算法  

Improved multi-objective ant colony algorithm for multi-objective minimum spanning tree

作　　者：高晓波[1] 

机构地区：[1]河池学院,广西宜州546300

出　　处：《计算机应用研究》2011年第2期474-476,共3页Application Research of Computers

摘　　要：多目标最小生成树问题是典型的NP问题。针对此问题,提出一种改进的多目标蚁群算法。为获得更好的非劣前端,通过合理选取多个信息素扩散源与扩散策略来避免其早熟收敛,并引入非支配排序算子,提高种群多样性并避免算法过早陷入局部最优解。对比实验结果表明：对于多目标最小生成树问题,该算法是有效的,不但在求解效率和解的质量方面优于相关算法,而且随着问题规模的扩大,算法仍保持较好的性能。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.

关 键 词：最小生成树 蚁群算法 多目标优化 信息素 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]