Optimisation of nursing human resources allocation in large hospitals based on improved particle swarm optimisation algorithm

In this paper, an optimisation configuration model based on an improved particle swarm optimisation algorithm is proposed to address issues such as supply-demand imbalance in the allocation of nursing human resources in large hospitals.Firstly, a multi-objective optimisation function is constructed with the core of total work efficiency and job matching degree, comprehensively considering human cost, resource consumption, salary expenditure, and nurse competence, to achieve dual optimisation of resource efficiency and job adaptation.Secondly, innovatively introducing the Metropolis criterion of simulated annealing algorithm and the crowding factor of artificial fish swarm algorithm.Finally, by improving the algorithm to solve the multi-objective function, output a resource allocation plan that meets the requirements of nursing load balance and job requirements.The experimental results show that the proposed method consistently maintains excellent performance of over 90% in scheduling coverage and 0.88-0.95 in shift balance index testing.