Employee absences are inevitable in practice due to illness, heavy workloads or accidents. These unforeseen events result in the disruption of employee shift rosters, which are then typically repaired using re-rostering methods. Despite their widespread use, repair methods often require last-minute changes to rosters, negatively affecting employees’ personal lives. Robust rosters are thus crucial when it comes to minimizing the negative impact of these unforeseen events. The academic literature, however, currently lacks a metric capable of measuring the robustness of staff rosters. This study introduces two complementary approaches for quantifying roster robustness without the use of simulation. The first metric enables an a priori estimation of how well unexpected employee absences can be accommodated, while the second metric approximates the costs incurred by repair methods. An integer programming-based methodology is proposed for generating robust rosters in a controlled manner. A computational study using public instances based on real-world scenarios demonstrates the effectiveness of the proposed methodology. A significant reduction of costs is observed when enforcing an appropriate level of robustness, compared against when robustness is ignored.

在实践中，由于疾病、繁重的工作量或事故，员工缺勤是不可避免的。这些不可预见的事件导致员工轮班名册中断，然后通常使用重新排班的方法进行修复。尽管它们被广泛使用，但修复方法通常需要在最后一刻更改名册，从而对员工的个人生活产生负面影响。因此，要尽量减少这些不可预见事件的负面影响，强大的名单至关重要。然而，学术文献目前缺乏能够衡量员工名册稳健性的指标。本研究介绍了两种互补的方法，用于在不使用模拟的情况下量化名册稳健性。第一个指标能够对意外员工缺勤的适应程度进行先验估计，而第二个指标近似于修复方法产生的成本。提出了一种基于整数规划的方法，用于以受控方式生成健壮的名册。使用基于真实世界场景的公共实例的计算研究证明了所提出方法的有效性。与忽略鲁棒性时相比，在强制执行适当级别的鲁棒性时，可以观察到成本的显着降低。