Optimizing palliative home healthcare: A routing and scheduling model with emotional burden and patient-caregiver preferences

The increasing demand for personalized and human-centered care in home-based palliative services necessitates efficient yet empathetic healthcare logistics solutions. This study addresses the Palliative Home Healthcare Caregiver Routing and Scheduling Problem with Emotional Consideration (PHHCRSP-E), aiming to optimize the daily assignment and routing of nurses visiting patients in home-based palliative care. The model minimizes a weighted sum of total travel time and emotional imbalance among nurses, subject to operational constraints such as service durations, time windows and nurse workload limits. A mixed-integer linear programming (MILP) formulation is proposed, incorporating subtour elimination and emotional burden balancing. The model is implemented on a synthetic dataset consisting of five patients and two nurses, with each patient characterized by spatial coordinates, service requirements, time preferences, and an emotional burden score. Results demonstrate the model’s capability to provide feasible and balanced nurse–patient assignments while respecting logistical and psychosocial constraints. By embedding emotional dynamics directly into care planning, this study contributes a novel and human-centered perspective to healthcare logistics and supports more empathetic, data-driven decisions in palliative home care services.