Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/325784 
Year of Publication: 
2024
Citation: 
[Journal:] Operations Research Perspectives [ISSN:] 2214-7160 [Volume:] 12 [Article No.:] 100302 [Year:] 2024 [Pages:] 1-19
Publisher: 
Elsevier, Amsterdam
Abstract: 
Home Health Care (HHC) services are essential for delivering healthcare programs to patients in their homes, with the goal of reducing hospitalization rates and improving patients' quality of life. However, HHC organizations face significant challenges in scheduling and routing caregivers for home care visits due to complex criteria and constraints. This paper addresses these challenges by considering both caregiver assignments and transportation logistics. The objective is to minimize the total travel distance and CO2 emissions while ensuring a balanced workload for caregivers, meeting patients' preferences, synchronization, precedence, and availability constraints. To tackle this problem, we propose a multiperiodic Green Home Health Care (GHHC) framework. In the first stage, we utilize multiobjective programming and the NSGA-II algorithm to generate Pareto front solutions that consider travel distance and CO2 emissions. In the second stage, a Mixed-Integer Linear Programming (MILP) model is proposed to balance caregivers' workload by assigning them to the patient routes generated in the first stage. The results highlight the trade-off between shorter routes and lower emissions. Furthermore, we examine the impact of prioritizing continuity of care and patient satisfaction. This research provides valuable insights into addressing the scheduling and routing challenges in HHC services, contributing to a more efficient and environmentally friendly healthcare delivery.
Subjects: 
Green Home Health Care
Mixed integer linear programming
Multiobjective optimization
NSGA-II
Synchronization constraints
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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