关键词: 云制造, 知识服务, 服务组合, 聚类分析, 关联规则挖掘, 多中心涡流搜索算法

Abstract: Aiming at the optimization problem of knowledge service composition under cloud manufacturing,a service composition and optimization model with time,cost,availability,accuracy,innovation and credibility as the optimization objective was established with the the strategy of QoS-aware service composition by analyzing the process of service composition and optimization.The search space was pre-processed by using clustering analyse and association rule mining strategy,which contributed to reducing the search space and achieving identifying and matching of knowledge service resources quickly and accurately,and improving the efficiency and success rate of knowledge service composition.Aiming at the problem that standard vortex search algorithm is easy to fall into local minimum,an improved mutiple centre vortex search algorithm was proposed for global optimization of service composition problem.Simulation results showed that the combination of clustering analyse and association rule mining strategy with multi center vortex search algorithm could greatly shorten the search time and get better solution,and can solve the optimization problem of knowledge service composition more effectively.

Key words: cloud manufacturing, knowledge service, service composition, clustering analyse, association rule mining, mutiple centre vortex search algorithm