Crew Scheduling Problems: A Systematic Literature Review

In industries such as airlines, railways, and healthcare, crew scheduling presents a critical optimization concern. Crew scheduling involves assigning employees to cover a set of flights, train trips, or hospital shifts over a planned period. The procedure is also subject to complex regulations and operational constraints. Although several reports have documented issues regarding crewscheduling, the studies were not thorough and recorded insufficient data on contemporary optimization approaches and their effectiveness. In this study, 142 papers were reviewed to address the knowledge gap. The focus in this study was predominantly on literature published since 2010. Firstly, crew scheduling definitions were presented, which distinguished between crewmodes. Subsequently, a classification of the reviewed literature based on solution methods was discussed. This systematic review identified pertinent studies from four electronic databases: Scopus, IEEE Xplore, ScienceDirect, and Springer per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Specific criteria were applied to precisely determine which empirical criteria to include or exclude. The findings from this study offered promising recommendations and possible directions for future research. Furthermore, the current state of machine learning-based hyper-heuristic optimization in solving crew scheduling issues was underscored.