基于动态匹配网络的制造服务组合自适应方法

Manufacturing Service Composition Self-Adaptive Approach Based on Dynamic Matching Network

云制造(cloud manufacturing,简称CMfg)模式下,制造任务和制造服务都处于动态变化的环境中,制造服务组合的动态适应能力问题亟待解决.针对这一问题,以制造任务和制造服务的匹配关系为基础,构建了制造任务-制造服务动态匹配网络(dynamic matching network,简称DMN)理论模型,在此基础上提出了一种三阶段的制造服务组合自适应方法(three-phase manufacturing service composition self-adaptive approach,简称TPMSCSAA).第1阶段通过负载队列模型对QoS进行动态评估,以负载和动态QoS为优化目标,将最优制造服务组合问题转化为制造服务网络中最短路径的搜索,实现制造服务的动态调度;第2阶段对不同类型的制造任务和制造服务变更进行实时获取,同步更新制造任务网络和制造服务网络;第3阶段触发动态调度算法,完成动态匹配边的重构.最后,通过对电梯设计服务组合的实验仿真,验证了方法的可行性和有效性.

In cloud manufacturing （CMfg） model, both manufacturing tasks and manufacturing services are in a dynamic environment, therefore the dynamic adaptability of the manufacturing service composition needs to be solved urgently. To address this problem, a theoretical model for manufacturing task and manufacturing service dynamic matching network （DMN） is constructed based on the matching relationships between manufacturing tasks and manufacturing services. Based on this model, a three-phase manufacturing service composition self-adaptive approach （TPMSCSAA） is proposed in this paper. Firstly, by using the load and dynamic QoS evaluated by the load queue model as the optimization goals, the optimal manufacturing service composition is transformed into the shortest path search in the manufacturing service network, and thus dynamic scheduling of manufacturing service composition is realized. Secondly, the changes of manufacturing tasks and manufacturing services are obtained to refresh the manufacturing task network and manufacturing service network in real time. Thirdly, the dynamic scheduling algorithm is triggered to complete the reconstruction of the dynamic matching edges. Finally, the experimental simulation of elevator design service composition is carried out to validate and verify the proposed approach.