Article: Optimisation of nursing human resources allocation in large hospitals based on improved particle swarm optimisation algorithm Journal: International Journal of Business Intelligence and Data Mining (IJBIDM) 2026 Vol.28 No.9 pp.26 - 42 Abstract: 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. Inderscience Publishers - linking academia, business and industry through research

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

Authors: Su Yuan; Wan Qing Liang; Duoduo Yu; Huan Liu; Yingnan Tian

Addresses: Department of Human Resources Management, The People's Hospital of Yubei District of Chongqing, Chongqing, 401120, China ' Department of Business Administration, School of Economics and Management, Xidian University, Xi'An, 710126, China ' School of Nursing and Health Studies, Hong Kong Metropolitan University, Hong Kong, 999077, China ' Department of Social Medicine, School of Public Health, Harbin Medical University, Harbin, 150081, China ' Department of Social Medicine and Health Management, School of Public Health, Chongqing Medical University, Chongqing, 400016, China

Abstract: 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.

Keywords: improved particle swarm algorithm; large hospitals; nursing human resources; optimise configuration.

DOI: 10.1504/IJBIDM.2026.154233

International Journal of Business Intelligence and Data Mining, 2026 Vol.28 No.9, pp.26 - 42

Received: 05 Nov 2025
Accepted: 02 Feb 2026
Published online: 17 Jun 2026 *

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

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