摘要
针对基本蚁群算法在求解QoS选播路由问题中存在的容易陷入局部最优和收敛速度慢的缺陷,提出一种基于自适应节点选择的蚁群算法对该问题进行求解.该算法根据解的情况自适应调整节点选择策略;依据各路径上信息素的"集中"程度判断解的早熟、停滞情况,并对可能陷入局部最优的解进行信息素混沌扰动更新,以便跳出局部极值区间.仿真实验表明,算法全局搜索能力较强,能够跳出局部极值区间,快速地收敛到全局最优解,算法是可行、有效的.
Ant colony algorithm is easy to fall in local best and its convergent speed is slow in solving multiple QoS constrained anycast routing problems.Therefore,an adaptive nodes selection ant colony algorithm is proposed in this paper to solve the problems.The nodes selection strategy is adjusted adaptively according to the solution.Stagnation behavior is judged by the concentration level of the pheromone on the path.Chaos perturbation is utilized to update the pheromone trail on the path in order that solutions which may fall into local optimum can range out of local best.According to simulations,Its global search is strong and it can range out of local best and it is fast convergence to the global optimum.The improved algorithm is feasible and effective.
出处
《微电子学与计算机》
CSCD
北大核心
2011年第8期112-115,118,共5页
Microelectronics & Computer
基金
广西自然科学基金项目(2010GXNSFA013127)
广西教育厅科研项目(201010LX076)
关键词
蚁群算法
QoS选播路由
自适应节点选择
混沌扰动
ant colony algorithm
QoS anycast routing
adaptive nodes selection
chaos perturbation
