【摘要】 工作流的调度问题因为含有多个目标的限制因素,属于非确定性(NP)问题.本文通过将工作流模型分层,提出一种优化调度算法.算法分为两大阶段,检测阶段通过循环加工提高生产质量;虚拟阶段将各制约节点不断迭代虚拟成一个虚拟节点,将服务抽象化,最终简化服务的选择问题.对比发现,在相同实验环境下,本算法相比传统最小关键路径算法具有一定优越性.更多还原

【Abstract】 The scheduling of workflows is a well-known non-deterministic( NP) problem because it contains multiple targets constraints. This paper proposed a time-quality optimization scheduling algorithm by layering the workflow model into three layers, such as mapping layer,dominant layer, and decision layer, respectively. The algorithm has two stages, stage one is called detection, it can improve the production quality by means of cycle machining in this stage; another stage is virtualization,which uses iterative way to virtualize nodes in mutual constraints into a new virtual node, abstracts the services,and simplifies the selection of services eventually. In comparison, the proposed algorithm was more effective than the traditional minimum critical path algorithm in the same experimental environment.更多还原