仿生柔性工作流建模与适应算法研究*

为提高柔性工作流对外界动态变化的响应速度，将生物的反射机理引入柔性工作流，构建了柔性工作流神经网络系统。模仿生物响应外界刺激的反射机理，利用人工神经网络技术，在柔性工作流中建立了仿生柔性工作流模型，定义了该模型中的人工神经网络概念模型，并以该模型为基础，提出了柔性工作流适应算法框架。最后，以企业生产计划节点工时定额的制定为例，构建了处理元群为BP网络的仿生柔性工作流模型，对柔性工作流适应算法进行仿真。仿真结果显示，建立的模型能够根据参数的动态变化作出正确的响应，从而证明仿生柔性工作流适应算法能够智能响应外

Study on bionic flexible workflow modeling and adaptation algorithm

To improve the responding speed of the flexible workflow to the external dynamic changes, introduced the biological mechanism of reflection into the flexible workflow, builded the neural network system in the flexible workflow. By using of the biological mechanism of reflection to the stimulus, the bionic flexible workflow model is created and the concept model of artificial neural network is defined in a flexible workflow with artificial neural network technology, then, proposed a framework of flexible workflow adaptation algorithm based on the above model. Finally, with an example of working hour quota set in the enterprise production planning node, simulated the flexible workflow adaptation algorithm based on the bionic flexible workflow model which the type of the processing neural group is BP model. Simulation results show that the established model can make correct response to the dynamic changes according to the parameters, thus proving the adaptation algorithm of bionic flexible workflow can respond to outside dynamic change intelligently.