融合遗传蚁群算法的Web服务组合研究

Based Web Service Composition with Genetic Algorithm and Ant Colony Optimization

为了提高Web服务组合流程中服务选择技术的收敛性能,提出了一种基于遗传算法与蚁群算法相融合的多目标优化策略,用于解决基于QoS的Web服务组合问题。本文首先将Web服务组合的全局最优化问题转化为寻求一条QoS最优解的路径问题,并通过改进遗传算法得到蚁群算法中初始路径的信息素分布,再通过改进蚁群算法来求得最优解。仿真实验结果表明,该改进算法能在较少的进化代数下得到最优路径,提高了Web服务组合的快速全局搜索能力。

To improve the convergence ability of service selection technology in process of Web service composition, the paper presents a multi-objective optimization strategy based on genetic algorithm and ant colony algorithm to solve global optimization problem in QoS-based Web service composition. In the paper, global optimization problem in Web service composition is presented as a QoS optimal routing problem. And then, an improved genetic algorithm is proposed to get pheromone distribution in initial route of ant colony algorithm. At last, an improved ant colony algorithm is presented to get the optimal solution. Simulation result suggests that the improved algorithms can get the optimal routing in less evolutional generation than typical algorithms, and improve global research ability in Web Service composition.