Optimization of the electric home healthcare routing and scheduling problem with heterogeneous fleet, and synchronized jobs having time windows

In this study, we work on the home healthcare routing and scheduling problem with heterogeneous electric vehicles, fast chargers and synchronized jobs having time windows. The problem aims to establish daily routes and schedules for healthcare nurses to provide a variety of services to patients located at a scattered area. Each nurse should be assigned to an electric vehicle from a heterogeneous fleet of vehicles to perform the assigned jobs within working hours. We consider three different types of vehicles in terms of battery capacity and energy consumption. We aim to minimize the total cost of energy consumption, fixed nurse cost, and costs arising from the patients that cannot be served within the working day. A mixed integer programming formulation is developed for the problem. In addition, an adaptive variable neighborhood search (AVNS) algorithm, which successfully integrates greedy random adaptive search procedure (GRASP) heuristic is proposed. The heuristic employs a set of advanced efficient procedures tailored to handle the complex structure of the problem. In order to evaluate the performance of the proposed heuristic its results are compared with those of the mathematical model. We also conduct extensive experiments to analyze the problem and its parameters.