计算机工程 ›› 2009, Vol. 35 ›› Issue (10): 182-187.doi: 10.3969/j.issn.1000-3428.2009.10.060

• 人工智能及识别技术 • 上一篇    下一篇

蚁群算法在Web服务组合中的应用

彭晓明1,2,何炎祥1,朱兵舰3   

  1. (1. 武汉大学计算机学院,武汉 430072;2. 空军雷达学院预警监视情报系,武汉 430019;3. 空军雷达学院研究生管理大队,武汉 430019)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-05-20 发布日期:2009-05-20

Application of Ant Colony Algorithm in Web Services Composition

PENG Xiao-ming1,2, HE Yan-xiang1, ZHU Bing-jian3   

  1. (1. School of Computer, Wuhan University, Wuhan 430072;2. Department of Early Warning Surveillance Intelligence, Airforce Radar Academy , Wuhan 430019;3. Department of Graduate Management, Airforce Radar Academy, Wuhan 430019)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-05-20 Published:2009-05-20

摘要: 为了在服务组合过程中高效地发现、选择满足用户要求的Web服务,提出基于蚁群算法的多目标优化组合用以实现用户对组合服务质量的需求。该方法根据不同Web服务的QoS属性指标,选择相应的Web服务得到Pareto最优解集合,用户根据实际需要或对目标函数的偏好,从Pareto最优解集中挑选一个或多个解作为组合服务质量问题的最优解,从而形成最后的决策方案。从理论和实验2个方面与相关研究成果进行分析比较。

关键词: 蚁群算法, 多目标优化, Web服务, 服务质量

Abstract: In order to find and select the appropriate Web services meeting the requirements of users efficiently in the process of Web services composition, this paper uses multi-objective optimization based on Ant Colony Algorithm(ACA) to achieve the users’ requirement of the Quality of Service(QoS) composition. According to the properties of Web services, the appropriate Web service is selected and the Pareto optimal solutions set is gained. One or more solutions are selected as the optimal solution from the Pareto optimal solutions set, and the decision project is formed. It is compared with the corresponding research from theory and experience.

Key words: Ant Colony Algorithm(ACA), multi-objective optimization, Web services, Quality of Service(QoS)

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