摘要
提出一种改进的蚁群算法并将其应用于Web服务选择问题中.该算法使用非线性动态变化的伪随机比例选择参数及蚂蚁多重最优解随机加权路由选择算法控制蚁群的行为,使用5维Web服务质量向量和蚁群适应度函数评价蚂蚁构造的路径质量,蚂蚁根据其构造的路径质量进行信息素更新;该算法使蚁群在其解空间的进化能力得到很大的提高.实验证明,该算法在Web服务选择问题上比传统的蚁群算法效率更高.
Focusing on Web service selection problem, a new modified ant colony optimization （ACO） algorithm is proposed. Both a nonlinear dynamic parameter of the pseudorandom proportion selection rule and a multiple-optimal-solution random-weighted route selection algorithm are employed in the algorithm proposed to control the behavior of ant colony. Besides, a five-dimensional service quality vector and the fitness function are used in the algorithm to evaluate the ant solutions, and each ant updates the pheromone according to the quality of their solutions they built. With these measures, the evolution ability of ant colony can be significantly improved. The experimental results show that the proposed algorithm outperforms traditional ACO algorithms.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2014年第8期1107-1111,共5页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(61170168
61170169
61100028)
中央高校基本科研业务费专项资金资助项目(N110404017)
关键词
服务选择
蚁群算法
随机加权路由选择
动态伪随机比例选择参数
算法性能评价指标
service selection
ant colony optimization
random-weighted route selection
dynamic pseudorandom proportion selection parameter
algorithm performance evaluation index
