This work focuses on the study of robust no-wait flow shop scheduling problem (R-NWFSP) under the interval-valued fuzzy processing time, which aims to minimize the makespan within an upper bound on total completion time. As the uncertainty of actual job processing times may cause significant differences in processing costs, a R-NWFSP model whose objective function involves interval-valued fuzzy sets (IVFSs) is proposed, and an improved SAA is designed for its efficient solution. Firstly, based on the credibility measure, chance constrained programming (CCP) is utilized to make the deterministic transformation of constraints. The uncertain NWFSP is transformed into an equivalent deterministic linear programming model. Then, in order to tackle the deterministic model efficiently, a simulated annealing algorithm (SAA) is specially designed. A powerful neighborhood search method and new acceptance criterion are applied to find better solutions. Numerical computations demonstrate the high efficiency of the SAA. In addition, a sensitivity analysis convincingly shows that the applicability of the proposed model and its solution strategy under interval-valued fuzzy sets.

中文翻译：

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区间值模糊处理时间下无等待流水车间调度的机会约束规划方法

这项工作的重点是研究在区间值模糊处理时间下的鲁棒无等待流水车间调度问题（R-NWFSP），其目的是在总完成时间的上限内最小化制造时间。由于实际工作处理时间的不确定性可能会导致处理成本的显着差异，因此提出了一种目标函数涉及区间值模糊集（IVFS）的R-NWFSP模型，并针对其有效解决方案设计了一种改进的SAA。首先，基于可信度度量，利用机会约束规划（CCP）进行约束的确定性转换。不确定的NWFSP被转换为等效的确定性线性规划模型。然后，为了有效地处理确定性模型，专门设计了一种模拟退火算法（SAA）。应用了功能强大的邻域搜索方法和新的接受准则来找到更好的解决方案。数值计算证明了SAA的高效率。此外，敏感性分析令人信服地表明，所提出的模型及其求解策略在区间值模糊集下的适用性。