A review on metaheuristics for solving home health care routing and scheduling problems

IF 7.2 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Applied Soft Computing Pub Date : 2025-07-05 DOI:10.1016/j.asoc.2025.113560

Yaping Fu , Jie Dong , Kaizhou Gao , Ponnuthurai Nagaratnam Suganthan , Min Huang , Lihua Zhu

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引用次数: 0

Abstract

Nowadays, the healthcare of elderly people catches wide attention since the increase of aging population puts significant pressure on public medical resources. The population aging and scarce care resources are likely to result in a substantial increase in demand for home health care (HHC) services. In order to improve operation efficiency and reduce service cost, home health care routing and scheduling problems (HHCRSPs) have received many concerns from academia and industry in recent years. HHC provides care services to customers and elderly at their homes by assigning proper caregivers and resources as their requirements. Due to the large scale and strong coupling features, as well as various practical requirements in concrete scenarios, there exist a great many of challenges in addressing the HHCRSPs effectively. Recently, metaheuristics have been employed and made breakthroughs in solving such difficult HHCRSPs. This article aims to provide a comprehensive literature review of metaheuristics for handling HHCRSPs. The existing studies regarding HHCRSPs are firstly summarized and analyzed from the perspectives of optimization objectives, number of objectives, uncertainties, constraint conditions, and number of care centers. Next, the metaheuristic algorithms for handling the HHCRSPs are summed up and dissected from the views of classifications, solution encoding and decoding, ensemble of metaheuristics and local search strategies, test instances, performance metrics, statistical analysis, and stopping criteria. Subsequently, challenges of addressing the HHCRSPs are analyzed and discussed. Afterwards, we point out future research directions and significant research contents. Finally, we conclude this research.

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元启发式方法在解决家庭医疗照护路线与调度问题上的研究综述

随着人口老龄化的加剧，对公共医疗资源的压力越来越大，老年人的健康问题受到了广泛的关注。人口老龄化和护理资源稀缺可能导致家庭保健服务需求的大幅增加。为了提高运营效率，降低服务成本，家庭医疗路径调度问题近年来受到学术界和产业界的广泛关注。HHC根据客户和老年人的需要，分配适当的护理人员和资源，在他们家中为他们提供护理服务。由于其规模大、耦合强的特点，以及具体场景下的各种实际需求，在有效解决hhcrsp时存在着许多挑战。近年来，元启发式方法在解决这类难题方面取得了突破。本文旨在对处理hhcrsp的元启发式方法进行全面的文献综述。首先从优化目标、目标数量、不确定性、约束条件、护理中心数量等方面对现有的hhcrsp研究进行了总结和分析。其次，从分类、解编码和解码、元启发式算法与局部搜索策略的集成、测试实例、性能指标、统计分析和停止准则等方面对处理hhcrsp的元启发式算法进行了总结和剖析。随后，分析和讨论了解决hhcrsp的挑战。最后指出了今后的研究方向和重要的研究内容。最后，对本研究进行总结。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Soft Computing 工程技术-计算机：跨学科应用

CiteScore

15.80

自引率

6.90%

发文量

874

审稿时长

10.9 months

期刊介绍： Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities. Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.