考虑老年人满意度的多目标居家养老护理员路径优化

doi:10.3969/j.issn.1007-7375.2021.01.010

摘要/Abstract

摘要： 居家养老服务是适应我国国情的养老模式，在推进养老服务发展的同时，必须提高养老服务质量，合理优化服务资源。以居家养老服务的实际需求为关注点，首先在考虑居家养老服务中心运营成本的基础上，构建基于前景理论的符合老人心理特征的服务满意度函数，建立最大化满意度和最小化成本的多目标养老护理员调度模型；然后利用改进的遗传算法求Pareto最优解集；最后通过算例分析得出老人对时间窗的敏感性越低时服务满意度越高，而当服务满意度提高到一定的程度时需要更多的成本来支撑，此外与传统遗传算法相比，运营成本相同下服务满意度提高了约10%。不仅为管理者提供了有效的权衡决策，同时提升了老年人的服务满意度。

关键词: 居家养老护理员, 老年人满意度, 路径优化, 前景理论, 多目标遗传算法

Abstract: Home-health-care is a model of elderly care that suits China's national conditions. While promoting the development of home-health-care, The quality of home-health-care must be improved, and the service resources reasonably optimize, focusing on the actual needs of home-health-care. Firstly, based on the operating cost of home-health-care centers, a service satisfaction function is constructed based on prospective theory that meets the psychological characteristics of the elderly, and a multi-objective scheduling model established for home-health-care staff for the elderly that includes maximization of satisfaction and minimization of cost. Then using the improved genetic algorithm, the Pareto optimal solution set is found; Finally, the analysis of the example shows that the elderly's service satisfaction is higher when their sensitivity to time window is lower, and when the service satisfaction is increased to a certain degree, more costs are needed to support it. In addition, compared with the traditional genetic algorithm, the service satisfaction is increased by about 10% when the operating cost is the same. It not only provides effective decision support for managers, but also improves the service satisfaction of the elderly.

Key words: home-health-care staff for elderly, elderly satisfaction, routing optimization, prospect theory, multi-objective genetic algorithm

中图分类号:

F273
TP301

马跃如, 文铮, 易丹. 考虑老年人满意度的多目标居家养老护理员路径优化[J]. 工业工程, 2021, 24(1): 74-81,103.

MA Yueru, WEN Zheng, YI Dan. Multi-objective Home-health-care Staff for the Elderly Routing Optimization Considering Elderly Satisfaction[J]. Industrial Engineering Journal, 2021, 24(1): 74-81,103.

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