Optimization Models in Nurse Scheduling—A Review of Last Five Years

In a bustling hospital ward, the heart of healthcare beats in rhythms defined by nurses along with their shifts, their rest, their presence. But behind the calm of patient care lies a complex puzzle: how to ensure the right number of skilled nurses is available at the right time, every time. This paper takes readers through the evolving landscape of nurse scheduling, exploring 37 research studies in the Web of Science database published between 2020 and 2024. From hospitals overwhelmed by COVID-19 to digital systems learning to adapt in real-time, these studies reveal a silent yet critical battle, optimizing care through smarter rosters. This review categorizes the strategies from traditional optimization models to cutting-edge AI-driven systems and spotlights key challenges such as cost, real-time adaptability, and workforce satisfaction. The goal is simple yet profound: to support sustainable staffing that puts both patients and nurses at the center.