Abstract In this paper, an m-stage hybrid flow shop scheduling problem with limited workforce in charge of performing setup operations is addressed. Indeed, such workforce represents a critical resource since the number of workers assigned to each production stage is lower than the number of machines in the same stage. A novel discrete backtracking search algorithm powered by a tabu search operating through a new encoding structure, denoted as BSATS, is designed for the problem at hand. The proposed metaheuristic has been properly calibrated and then an exhaustive comparison analysis involving several evolutionary algorithms from the relevant literature has been carried out. Additionally, a mixed integer linear programming model has been formalized in order to optimally solve a set of small-sized test cases. The numerical results obtained, together with a consistent convergence analysis, confirm both the effectiveness and the efficiency of the proposed method.

中文翻译：

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有限人力资源约束下混合流水车间调度问题的求解

摘要 在本文中，解决了负责执行设置操作的劳动力有限的 m 级混合流水车间调度问题。事实上，这样的劳动力代表了一种关键资源，因为分配到每个生产阶段的工人数量低于同一阶段的机器数量。一种新颖的离散回溯搜索算法由通过新编码结构运行的禁忌搜索提供支持，表示为 BSATS，是为手头的问题设计的。所提出的元启发式算法已经过适当校准，然后对相关文献中的几种进化算法进行了详尽的比较分析。此外，混合整数线性规划模型已被形式化，以优化解决一组小型测试用例。得到的数值结果，