【摘要】 当前工作流系统普遍缺乏柔性,导致适应性和实用性较差.在工作流网(WF-Net)的基础上,增加了柔性场所和柔性迁移,提出了一种柔性工作流网(FWF-Net)的建模语言并对正确性进行了分析;同时在工作流系统中增加了建模和执行的交互学习机制,给出了学习的算法,使工作流系统从建模和执行都具有良好的柔性和适应性,同时降低复杂性.通过实验表明,不但能够实现柔性工作流系统,而且支持个性化的流程管理.更多还原

【Abstract】 Current workflow systems mostly lack flexibility, which lead to their adaptability and utilization are poor. The paper analyzes and classify the flexibility of workflow, presents a novel modeling language named Flexible Workflow Net (FWF-Net) that add flexible transition and place based on WF-Net, and proves its validity. Because interaction and machine learning are synthesized in the workflow system architecture, workflow modeling and enactment are both flexible, and the complexity of whole system is decrease. The prototype based on the model manifest that it not only realizes the flexible workflow, but also supports the personality of workflow.更多还原