Abstract: Through the production environment of simulated random jobs arrival,the periodic rescheduling strategy was used to allocate each job into corresponding schedule intervals.Aiming at the efficiency and stability,a multi-objective differential evolution algorithm based on Pareto solution was proposed to solve the scheduling optimization in every schedule interval,and a scheduling scheme was selected from the non-dominated solutions as the actual processing scheme.Under the different rescheduling period,the final makespan,the total tardiness,the total efficiency and the total stability obtained by scheduling the same number jobs with different arrival time were researched so as to guide the actual productive practices.

Key words: flexible job shop, dynamic scheduling, differential evolution, multi-objective optimization, Pareto solution

摘要： 为了研究柔性作业车间周期性再调度对生产稳定性和效率的影响,通过模拟随机工件到达的生产环境,运用周期性再调度的调度策略,将各个工件依次划入对应的调度区间,以效率和稳定性为目标,设计了一种基于Pareto概念的多目标差分进化算法对每个调度区间的工件进行调度优化,并从获得的非支配解集中采用决策策略选出一个调度方案作为实际调度加工方案。通过研究不同的再调度周期下与完工时间、总拖期、总效率和总稳定性之间的相互影响关系,有效地指导了实际生产实践。

关键词: 柔性作业车间, 动态调度, 差分进化算法, 多目标优化, Pareto解