The single-factory manufacturing is gradually transiting to the multi-factory collaborative production with the globalization. The decentralization of resources and the heterogeneity of the production modes make it difficult to solve this kind of problem. Therefore, the distributed assembly flexible job shop scheduling problem (DAFJSP) is studied. DAFJSP can be decomposed into several flexible job shop scheduling problems and several single machine factory scheduling problems. To begin with, a mixed integer linear programming model for the DAFJSP is formulated to minimize the earliness/tardiness and the total cost simultaneously. Then, an improved differential evolution simulated annealing algorithm (IDESAA) is proposed. The balanced scheduling algorithm is designed to trade off the two objectives. Two crossover and mutation operators are designed. Due to its strong robustness, simulated annealing is integrated to local search the best Pareto solutions. The greedy idea combined with the Non-Dominated Sorted selection is employed to select the offspring. Finally, comprehensive experiments are conducted and the results show that the proposed algorithm can solve DAFJSP effectively and efficiently.

中文翻译：

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一种改进的差分进化算法，用于解决分布式装配柔性作业车间调度问题

随着全球化，单工厂制造逐渐过渡到多工厂协同生产。资源的分散化和生产方式的异质性使得解决这类问题变得困难。因此，研究了分布式装配柔性作业车间调度问题（DAFJSP）。DAFJSP可以分解为几个灵活的车间调度问题和几个单机工厂调度问题。首先，制定了DAFJSP的混合整数线性规划模型，以最大程度地减少早期/延误和总成本。然后，提出了一种改进的差分进化模拟退火算法（IDESAA）。平衡调度算法旨在权衡这两个目标。设计了两个交叉和变异算子。由于其强大的鲁棒性，因此将模拟退火集成到本地搜索最佳的Pareto解决方案中。贪婪的想法与非支配排序选择相结合，被用来选择后代。最后，进行了综合实验，结果表明所提算法能够有效，高效地解决DAFJSP问题。