A Hypermutation Genetic Algorithm for the Dynamic Home Health-Care Routing Problem

The Home Health-Care (HHC) is to provide medical services to patients in their home in order to reduce pressure in hospitals. These services requires the medical staff to be driven to several patients' location while respecting a certain schedule, patients' health emergency, and minimizing the traveled cost. Accordingly, determining the best itinerary for visiting patients can be considered as a vehicle routing problem. In this paper, we investigate the Dynamic Vehicle Routing Problem for Home Health care (D-HHC). The D-HHC aims to determine the minimum cost route that allows the medical staff to provide medical services to a set of dispersed patients via a fleet of caregivers starting from a starting point (the hospital), while considering real-time requests. This means that new calls from patients could arrive after the departure of the caregiver and its route have to be readapted to include these new patients. To deal with the problem, a Hypermutation Genetic Algorithm (HGA) is proposed. The performance of the HGA is evaluated based on Solomon benchmarks. The experimental results show that our proposal outperforms the existing approaches in most cases.