Optimization of the technician routing and scheduling problem for a telecommunication industry

This paper proposes two models for the Technician Routing and Scheduling Problem (TRSP), which are motivated by a telecom provider based in Saskatchewan, Canada. The proposed TRSP models are distinguished from existing models by their ability to address two key issues: overnight and lunch break scheduling. The models aim to scheduling a set of technicians with homogeneous skill levels and different working hours for the purpose of providing services with different service times and time windows to a diverse set of widely spread communities. As the large-sized experiments of this problem categorized into NP-hard problems, a metaheuristic-based technique, Invasive Weed Optimization, is developed to solve them. A comparative analysis is performed to choose the optimum TRSP model based on two factors which are distance of communities to the main depot and balanced service times during planning horizon. The performance of the models is evaluated through the real-world data obtained from the telecom provider. The results prove that the overnight TRSP model is capable of substantially decreasing travel costs and the number of technicians that are required to perform the same set of services.