Operating room scheduling is a complex process that involves various resources and takes the interests of many parties into consideration. The genetic algorithm is the frequently used metaheuristic algorithm to solve a large-size operating room scheduling problem. Many techniques have been developed to improve the genetic algorithms' performance in dealing with the operating room scheduling complexity. In this paper, we survey available literature to identify improvement techniques used at each stage of the genetic algorithm and capture the underlying problems. This review provides a mapping of improvement techniques in genetic algorithms correlating with the considered problems. The results can be employed by other researchers as a guide for future research in integrating a genetic algorithm or other population-based metaheuristic algorithm with a recent heuristic algorithm following the future directions of operating room scheduling research.