A two-stage modeling with genetic algorithms for the nurse scheduling problem

This study develops a two-stage mathematical modeling for a nurse scheduling system wherein hospital management requirements, government regulations, and nursing staffs’ shift preferences are incorporated. In the first stage, the nurse work and vacation schedules are arranged and genetic algorithm (GA) is used to solve for the optimal schedules and to check for any violation of government regulations, hospital management requirements, and the scheduling fairness. In the second stage, the nurse roster schedule is arranged and GA is further adopted to solve the optimal schedule. An empirical case study is performed and the results show that GA can be an efficient tool for solving the nurse scheduling problem. In addition, it can also be easily modified to suit different cases encountered in hospitals.