A bi-objective Smart Capacitated Vehicle Routing Problem with Threshold Waste Level for the Home Health Care.

This article presents a bi-objective mixed-integer linear programming (MILP) model for solving the smart capacitated vehicle routing problem with threshold waste level (SCVRP-TWL) with a specific application in home health care services waste management. The model aims to optimize the route of the vehicles for the purpose of minimizing both the total travel time and the total carbon emission. The data used in the model are randomly generated, based on the real coordinates of Dublin city. The results of the model are visualized using the Google API direction tools. The research makes three key contributions to the field of vehicle routing and waste management. The integration of real-time traffic data and waste threshold level in the model, which allows for more accurate and efficient routing decisions. The application of the model in the unique domain of home health care (HHC) services waste management, which addresses a specific and important problem in this field. The use of the non-dominated sorting genetic algorithm II (NSGA-II) as the solution algorithm which allows for a better balancing of the trade-offs between the two objectives.