Nurse Scheduling Algorithms based on Different Scenarios

Abstract

This algorithm is based on a combination of integer programming, genetic algorithm, and decision tree to study nurse scheduling management problems in different scenarios. Firstly, the usage scenarios are classified based on the number of department members and energy levels. Then, the initial solution is obtained through integer programming based on information such as the actual energy level of nurses in the hospital. Finally, genetic algorithm is used to optimize the initial solution to obtain a final solution that is more in line with practical requirements. This algorithm can automatically classify or manually set use scenarios, and automatically obtain shift scheduling information by entering personalized parameters, which can meet the personal shift scheduling needs of nurses to the greatest extent, and can greatly reduce the high-frequency shift scheduling workload of Matron.