Multi-neighborhood simulated annealing for the home healthcare routing and scheduling problem

Over time, the focus on supportive and geriatric care has shifted from being predominantly provided in institutional settings like nursing or rest homes to be delivered within the homes of the patients. Trained caregivers now provide home healthcare services by visiting patients in their own homes and carrying out specific services based on each patient's individual needs before moving on to the next patient. Planning such a service involves considering the routing aspect and ensuring synchronization between services and designated time windows for patients. To solve the problem, we propose a local search approach that combines different neighborhood operators guided by the simulated annealing metaheuristic. Additionally, we introduce a realistic and diverse dataset and a robust and flexible file format based on JSON. This dataset and format have the potential to facilitate future comparisons and analyses. Our study shows that by appropriately tuning our algorithm in a statistically rigorous manner, it outperforms existing methods on all benchmarks.