<![CDATA[Nurse scheduling is a complex operational problem in healthcare systems due to the need to balance staffing requirements, operational efficiency, labor regulations, and workforce satisfaction simultaneously. Over the years, various optimization approaches have been developed to solve nurse scheduling problems, resulting in rapidly growing and diverse research trends. Therefore, this study aims to investigate the evolution of optimization approaches in nurse scheduling research using a Systematic Literature Review (SLR) combined with bibliometric analysis. The literature search was conducted using the Scopus database with the keywords “Nurse Scheduling”, “Nurse Rostering”, and “Nurse Scheduling Problem”. After applying several inclusion criteria, including publication year, document type, language, and subject area, 127 relevant journal articles were selected from an initial 835 articles. Bibliometric analysis was performed using VOSviewer version 1.6.20 through co-occurrence analysis, Network Visualization, and Overlay Visualization. The results indicate that nurse scheduling research has evolved from traditional mathematical programming approaches toward heuristic, metaheuristic, and hybrid optimization methods. Dominant research themes include optimization, integer programming, genetic algorithm, heuristic methods, and combinatorial optimization. The overlay visualization analysis further reveals emerging research trends related to healthcare scheduling, stochastic systems, decision-support integration, and human-centered optimization. This study contributes by providing a comprehensive overview of the evolution of optimization approaches in nurse scheduling research and identifying potential future research directions toward more adaptive, intelligent, and sustainable healthcare scheduling systems.]]>
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