• CN:11-2187/TH
  • ISSN:0577-6686

›› 2010, Vol. 46 ›› Issue (4): 169-176.

• 论文 • 上一篇    下一篇

资源约束下多过程的不确定时间建模与分析

杜彦华;范玉顺   

  1. 北京科技大学机械工程学院;清华大学自动化系
  • 发布日期:2010-02-20

Modeling and Analyzing of Uncertain Time for Multi-process of Workflows with Resource Constraints

DU Yanhua;FAN Yushun   

  1. School of Mechanical Engineering, University of Science and Technology Beijing Department of Automation, Tsinghua University
  • Published:2010-02-20

摘要: 由于测量不精确、信息不完备以及信息包含噪声等原因,工作流的时间信息会具有不确定性。针对不确定性情况下工作流时间建模和分析的实际需求,基于可能性理论,给出扩展模糊时间工作流网(Extended fuzzy timing workflow nets, EFTWFN)定义,实现对不确定性时间信息的全面描述。在考虑资源约束情况下,提出一种工作流多过程EFTWFN模型的推理分析方法,将EFTWFN与线性逻辑结合,定义多种变迁间的化简规则,再基于规则逐步化简EFTWFN模型,从而实现对不确定性时间问题的解决。所提出的方法实用性较强,能够有效处理资源约束情况下工作流多过程的定量和定性两方面问题;而且效率较高,可在线性时间复杂度内完成对问题的求解。在某制造企业中的实例应用与仿真验证表明,该方法具有很好的效果。

关键词: 不确定性, 多过程, 可能性理论, 线性逻辑, 资源约束

Abstract: Because of imprecise measurement, incomplete information, fuzzy or fault description, etc, the temporal information of some workflows is usually indeterminate (or uncertain). According to the actual need for uncertain temporal modeling and analysis in workflow system, based on possibility theory, the concept of extended fuzzy timing workflow nets (EFTWFN) is proposed, which can describe all uncertain temporal information in a workflow. Under the condition of considering resource constraints, the method to analyze multi-process of EFTWFN models is presented. First of all, several inference rules between transitions of workflows are defined on the basis of EFTWFN and linear logic. Then, the total model is reduced and analyzed gradually according to the rules. The method can solve the qualitative and quantitative problems for concurrent workflows with resource constraints. Furthermore, it has higher efficiency and can complete the process of inference in the linear time complexity. In the end, an application of the method is illustrated through an example in manufacturing enterprise and its validity is indicated by simulation.

Key words: Linear logic, Multi-process, Possibility theory, Resource constraint, Uncertainty

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