Research on Hospital Human Resource Allocation and Scheduling Based on Multi-objective Optimization Algorithm

Improving the level of human resource allocation in hospitals through algorithms is an effective way to deepen hospital reform. This paper elaborates on the importance of health human resource allocation and scheduling. Combined with the hospital’s human resource problem is modeled and its model is optimized. Based on particle swarm and 0-1 planning to improve relevant algorithms, the 0-1MOPSO algorithm model has been established that can effectively improve the level of multi-project staff deployment, and its advantages have been analyzed. The human resource allocation of the experimentally selected Y hospital is analyzed, and the effectiveness of the 0-1MOPSO algorithm in improving the multi-project staff deployment of Y hospital is verified through the comparison between the traditional PSO algorithm and the 0-1MOPSO algorithm. The experimental results show that the total efficiency nondominated solutions of 0-1MOPSO algorithm are between 187-242, 0-1MOPSO dominates most of the nondominated solutions of the traditional PSO algorithm, and the traditional PSO algorithm doesn’t dominate any of the nondominated solutions of 0-1MOPSO, which is able to provide a decision support with a lower total cost and higher total efficiency for the multi-project staff deployment in Hospital Y. The 0-1MOPSO algorithm model is a new model of the 0-1MOPSO algorithm, which is a new model of the traditional PSO algorithm. The 1MOPSO algorithmic model is applied to optimize the allocation and scheduling of hospital human resources.