Abstract: In the virtual cellular manufacturing environment, to solve the problem of deviation of the original scheduling scheme caused by the interference of emergency order, this paper aims at exploring how to deal with the emergency order through the similarity degree between processes, that is, maintaining the initial process of processing order as far as possible. It also develops rescheduling methodology, which adapts to emergency order and regular order production. To deal with the interference of emergency order, this paper establishes a multi-objective non-linear integer programming model, and it requires that completion time of the emergency order, total process time of the system and similarity degree between the processes should be considered at the same time. The available machine assembly and processing time assembly are set for the part which is ready to be processed. According to the arrival of the emergency order, the assembly can adjust at any time. Because the model is a non-linear integer programming, a hybrid optimization algorithm based on the combination use of Genetic Algorithm (GA) and Ant Algorithm (AA) is presented, that is, by means of genetic algorithm to find the feasible solution assembly of the model, and then use the ant colony algorithm to solve the optimal solution of the model. Finally, taking practical production of shipbuilding as example, the hybrid optimization algorithm based on the combination use of Genetic Algorithm (GA) and Ant Algorithm (AA) is verified to be feasible and effective, in which the reconfiguration model of considering similarity degree between the processes will be solved.

Key words: virtual cellular, rescheduling, similarity degree between processes, genetic-ant colony algorithm

摘要： 虚拟单元生产中,针对急件订单干扰情况,研究了考虑序位相似性,即尽量保持初始工序的加工次序的虚拟单元重调度问题。为了应对急件订单干扰,设置了各工件工序可用机器集合和相应的加工时间集合,构建了以序位相似性最大和急件订单完工时间、系统总流程时间最短为目标的多目标非线性整数规划模型。针对模型自身特征,采用了遗传—蚁群算法相结合的优化算法求解模型。最后,以船舶实际生产为例,验证了模型的可行和优越性,以及算法的有效性。

关键词: 虚拟单元, 重调度, 序位相似性, 遗传—蚁群算法