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基于模糊时间窗的多目标家庭医护人员调度研究
Multi-Objective Family Healthcare Worker Scheduling Study Based on Fuzzy Time Windows

DOI: 10.12677/mos.2025.141029, PP. 301-314

Keywords: 改进遗传模拟退火算法,护理人员调度,满意度,模糊时间窗
Improved Genetic Simulated Annealing Algorithm
, Caregiver Scheduling, Satisfaction, Fuzzy Time Windows

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Abstract:

为了向医疗服务中心的护理人员调度提供决策支持,研究考虑医患技能水平匹配,引入基于模糊时间窗的满意度函数来衡量患者的偏好满意度,构建患者满意度最大和路径成本最小的双目标家庭医护人员调度模型。针对多目标遗传算法的全局搜索能力和收敛速度不强等缺陷,采用改进PMX交叉算子更新个体位置,设计路径内两点交换邻域搜索算子以有效解决所提模型以及使用模拟退火进行变异操作以提升个体质量,防止陷入局部最优。通过与其它算法的实验结果进行对比,验证改进后的算法性能有效提高,求解结果更优。
To provide decision support to caregiver scheduling in healthcare service centers, the study considers doctor-patient skill level matching, introduces a fuzzy time window-based satisfaction function to measure patient preference satisfaction, and constructs a bi-objective home healthcare scheduling model that maximizes patient satisfaction and minimizes path cost. To address the shortcomings of the multi-objective genetic algorithm, such as the global search ability and weak convergence speed, the improved PMX crossover operator is used to update the individual positions, the two-point intra-path exchange neighborhood search operator is designed to efficiently solve the proposed model as well as the mutation operation using simulated annealing is used to improve the quality of the individuals to prevent them from falling into the local optimum. By comparing the experimental results with other algorithms, it is verified that the performance of the improved algorithm is effectively improved and the solution results are better.

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