In this work, we introduce a generalized flexible job-shop scheduling problem in which, besides the classical constraints of the flexible job shop scheduling problem other hard constraints such as machine capacity, time lags, holding times, and sequence-dependent setup times are taken into account. This problem is inspired by a real situation observed in a seamless rolled ring manufacturer. We propose a mixed integer linear programming (MILP) and a constraint programming (CP) models to represent the problem. Additionally, we develop a metaheuristic based on a Greedy Randomized Adaptive Search Procedure (GRASP) able to tackle efficiently large instances of the problem. The results show that CP outperforms the MILP and the proposed GRASP outperforms the CP when solving instances with more than 100 jobs.

在这项工作中，我们引入了一个广义的柔性作业车间调度问题，其中，除了柔性作业车间调度问题的经典约束之外，还采用了其他硬约束，例如机器容量、时间滞后、保持时间和依赖于序列的设置时间考虑到。这个问题的灵感来自在无缝轧制环制造商中观察到的真实情况。我们提出了一个混合整数线性规划（MILP）和一个约束规划（CP）模型来表示这个问题。此外，我们开发了一种基于贪婪随机自适应搜索程序 (GRASP) 的元启发式算法，能够有效地解决问题的大型实例。结果表明，在解决超过 100 个作业的实例时，CP 优于 MILP，并且所提出的 GRASP 优于 CP。