基于膜计算粒子群算法的多目标护理排班问题研究

Research on Multi-Objective Nursing Shift Scheduling Based on Membrane Computational Particle Swarm Algorithm

摘要

护理排班问题是一个复杂的多目标组合优化问题，需要同时优化多个相互冲突的目标，如护士工作负荷均衡性、班次偏好满足度、连续工作天数控制以及人力成本等. 传统优化方法在处理此类问题的规模和多目标特性时常面临挑战. 针对多目标护理排班问题的特点，提出了一种基于膜计算思想的改进粒子群优化算法(membrane computing-based particle swarm optimization, MCPSO). 将膜计算的结构化组织、并行演化及信息传递机制引入粒子群优化框架. 核心思想是利用膜结构对粒子种群进行分区管理，在不同膜空间内实施差异化的进化策略，并通过膜间通信规则促进不同子种群间优质解信息的交流与共享. 这种结构旨在增强算法在复杂解空间中的全局探索能力和局部开发能力，同时提升解的多样性和分布性，以更有效地逼近多目标问题的帕累托前沿. 实验结果表明，所提出的 MCPSO 算法在求解多目标护理排班问题上表现出良好的可行性和适应性，为求解复杂的多目标护理排班问题提供了一种融合膜计算思想的新思路.

Abstract

Nursing scheduling is a complex multi-objective combinatorial optimization problem that requires the simultaneous optimization of multiple conflicting objectives, such as nurse workload balance, shift preference satisfaction, control of consecutive working days, and labor costs. Traditional optimization methods often face challenges when dealing with the scale and multi-objective nature of such problems. This study addresses the characteristics of multi-objective nursing scheduling problems by proposing an improved particle swarm optimization algorithm based on membrane computing (Membrane Computing-based Particle Swarm Optimization, MCPSO). This algorithm incorporates the structured organization, parallel evolution, and information transmission mechanisms of membrane computing into the particle swarm optimization framework. The core idea is to use membrane structures to partition and manage the particle population, implement differentiated evolutionary strategies in different membrane spaces, and promote the exchange and sharing of high-quality solution information among different sub-populations through inter-membrane communication rules. This structure aims to enhance the algorithm's global exploration and local exploitation capabilities in complex solution spaces, while improving solution diversity and distribution to more effectively approximate the Pareto front of multi-objective problems. Experimental results demonstrate that the proposed MCPSO algorithm exhibits good feasibility and adaptability in solving multi-objective nursing scheduling problems. This study provides a new approach that integrates membrane computing concepts for addressing complex multi-objective nursing scheduling problems.

关键词

膜计算 / 粒子群优化算法 / 护理排班 / 多目标组合优化

Key words

membrane calculation / particle swarm optimization algorithm / nursing shift scheduling / multi-objective combinatorial optimization

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基金资助

国家自然科学基金资助项目(62362017)