Xiaomeng Ma , Xujin Pu , Yaping Fu , Kaizhou Gao , Yuchen Xu
{"title":"Home health care routing and scheduling problems considering patient classification and outsourcing: Modeling and a solution algorithm","authors":"Xiaomeng Ma , Xujin Pu , Yaping Fu , Kaizhou Gao , Yuchen Xu","doi":"10.1016/j.cor.2025.107143","DOIUrl":null,"url":null,"abstract":"<div><div>Home health care (HHC) is treated as a substitute for hospitalization and plays a crucial role in relieving the pressure of medical resources resulting from population aging. HHC routing and scheduling problems have received much attention in modeling and optimization fields. This paper proposes a multi-objective HHC routing and scheduling problem considering patient classification and outsourcing operation, in which patients are classified into two types, i.e., VIP patients and ordinary patients. All the patients are assigned to an HHC center or outsourced to third-party service providers. Then, the caregivers in the HHC center are scheduled to provide services for the assigned patients. First, a mixed integer programming model with minimizing total operation cost and minimizing total tardiness is established. Second, a Q-learning-based multi-objective evolutionary algorithm with problem-specific knowledge (QMEA-K) is specially devised. At last, numerous experiments are carried out by making comparisons between QMEA-K and four algorithms and an exact solver CPLEX. The acquired results prove the effectiveness and advantages of QMEA-K in tackling the concerned problem.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"182 ","pages":"Article 107143"},"PeriodicalIF":4.1000,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Operations Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0305054825001716","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Home health care (HHC) is treated as a substitute for hospitalization and plays a crucial role in relieving the pressure of medical resources resulting from population aging. HHC routing and scheduling problems have received much attention in modeling and optimization fields. This paper proposes a multi-objective HHC routing and scheduling problem considering patient classification and outsourcing operation, in which patients are classified into two types, i.e., VIP patients and ordinary patients. All the patients are assigned to an HHC center or outsourced to third-party service providers. Then, the caregivers in the HHC center are scheduled to provide services for the assigned patients. First, a mixed integer programming model with minimizing total operation cost and minimizing total tardiness is established. Second, a Q-learning-based multi-objective evolutionary algorithm with problem-specific knowledge (QMEA-K) is specially devised. At last, numerous experiments are carried out by making comparisons between QMEA-K and four algorithms and an exact solver CPLEX. The acquired results prove the effectiveness and advantages of QMEA-K in tackling the concerned problem.
期刊介绍:
Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.