Ozsakalli, GokberkOzturkoglu, OmerQadri, Syed Shah Sultan Mohiuddin2026-02-052026-02-0520251923-29261923-2934https://doi.org/10.5267/j.ijiec.2025.12.007https://hdl.handle.net/20.500.12416/15841This study addresses the daily scheduling and routing problem for home healthcare workers while incorporating lunch break requirements. The Home Healthcare Scheduling and Routing Problem is analysed alongside its common constraints, including patient and caregiver time windows, caregiver qualifications, and mandated breaks. To address this, four different variants of an effective Adaptive Large Neighbourhood Search (ALNS) algorithm were developed to provide high-quality solutions. The algorithms demonstrate significant efficiency, solving 30-patient instances optimally within an average of 12 seconds. For scenarios involving 100 patients, they maintained robust performance with a slight increase in computational time of about 54 seconds. Results indicate operational efficiency improvements of up to 36% through optimized travel routes and patient visitation schedules. To translate these findings into practice, a decision support system, the Home Healthcare Decision Support System (HHDSS), was designed to assist administrators by automating the complex task of scheduling and routing of caregivers. Tested using realistic patient data generated from Turkey, the system effectively allocates healthcare resources and improves responsiveness. Overall, the proposed framework shows strong potential as a valuable practical tool for improving the responsiveness and efficiency of home healthcare logistics. (c) 2026 by the authors; licensee Growing Science, Canadaeninfo:eu-repo/semantics/closedAccessHome HealthcareVehicle RoutingPersonnel SchedulingLunch BreakDecision Support SystemArticle10.5267/j.ijiec.2025.12.007