云制造环境下面向多任务的机床装备资源动态调度方法研究

iming at the characteristics of uncertainty and disturbance of machine tool dynamic scheduling in cloud manufacturing environment, a multi-taskoriented dynamic scheduling method is researched for machine tools. Combined with nonlinear process planning theory, an initial scheduling model is established with minimum time, cost, energy consumption and load balance degree, maximum service quality and reliability as goals. Using genetic variable neighborhood algorithm with elite strategy to solve the model. On the basis of considering the dynamic deviation, a dynamic scheduling strategy is proposed based on event driven and periodic rescheduling. An example is given to verify the validity of the model and the algorithm.