云制造模式下多目标柔性作业车间调度研究

Research on multi-objective flexible job shop scheduling under cloud manufacturing mode

为了解决实现云制造模式过程中的柔性作业车间调度问题,在进化算法的基础上提出了IM-MOEA/D算法。该算法为了减少运算,种群使用双编码模式,初始化种群分两步策略和六种规则,采用两类五种变邻域搜索并设置搜索阈值,以提升算法的全局和局部迭代寻优能力。最后用算例验证了IM-MOEA/D算法的有效性,有助于改善云制造环境下柔性作业车间调度的制造效率。

In order to solve the problem of flexible job shop scheduling when implementing the cloud manufacturing model,this paper proposes the IM-MOEA/D algorithm based on the decomposition-based multi-objective evolutionary algorithm.In order to reduce calculations,the algorithm uses dual coding for the population.Initializing the population is divided into a two-step strategy and six rules.It uses two types of five kinds of variable neighborhood search and sets the search threshold to improve the algorithm’s global and local iterative optimization capabilities.Finally,a calculation example is used to verify the effectiveness of the IM-MOEA/D algorithm,which is beneficial to improve the production efficiency of flexible job shop scheduling in the cloud manufacturing environment.