Utilizing the Internet of Things (IoT) to address uncertain home health care supply chain network

Generally, Home Health Care (HHC) consists of a medical team that serves patients in their own homes and carries out various medical services, such as taking biological samples and administering medicine. Aging trends in developing countries, and the growing tendency of the elderly to receive healthcare services in their own homes, leads to increasing demand for such services that outgrow those available in hospitals, healthcare personnel, and other resources. Therefore, HHC services and their associate demand rates are increasing dramatically. A major opportunity normally ignored in this regard is the applicability of the Internet of Things (IoT) systems to facilitate this practice. In this work, a two-phased approach is proposed to 1) identify the potential patients and 2) collect their biological samples and send them to be analyzed. Green Split Pick-up Vehicle Routing Problem (GSPVRP) and IoT concept are employed to address the patients in both sub-models. The proposed model is investigated by data from a real-world case study in Montreal, Canada, and solved using four multi-objective metaheuristic algorithms. An extensive analysis of the results revealed that utilizing the IoT system contributes to maximizing the overall occupancy rate of the vehicles and can effectively optimize the number of trips, hence minimizing total costs and greenhouse gas emissions.