Abstract: An improved multiple ant colony algorithm was presented which aims at load balance and optimization of network resources management. Through the interaction and dynamic update among the pheromone of multiple ant colony which are on behalf of the network traffic, the algorithm enabled network traffic to share a number of paths available; Through the combination of orientable choice and stochastic choice to select best path self-adaptively, the algorithm achieved the traffic load balancing; Through setting the maximum-minimum pheromone to avoid premature convergence, the algorithm increased capabilities of global optimum search; Through the improvement of the cost function and the comprehensive use of a variety of improved ways, the algorithm improved self-adaption of the algorithm. The results of simulation experiment demonstrate that compared with multiple ant colony load balance algorithm，improved multiple ant colony algorithm has superiority in reducing time of auto adaption, lowering packet loss rate and improving efficiency of load balance.

Key words: Ant colony algorithm , Load balancin ,  Network resource optimization 

摘要： 针对网络资源管理中的负载均衡与优化问题,提出一种改进的多蚁群算法,通过代表网络流量的多
蚁群间信息素的相互作用和动态更新来实现网络流量分担到多条可用路径;通过确定性选择和随机性选择相结合
的方法自适应地选择最优路径,实现流量负载均衡;通过设置信息素的最大和最小值,避免早熟收敛行为,增加了全
局最优解的搜索能力;通过对代价函数的改进及以上改进方法的综合运用提高了算法的自适应性。仿真实验结果
表明,改进的多蚁群算法比原多蚁群算法在缩短自适应时间、减少丢包率、提高负载均衡效率方面具有更优的性能。

关键词: 蚁群算法 , 负载均衡 , 网络资源优化