Scalable Planning of Garbage Collection in a Smart City

George Daoud, Mohamed El-Darieby

Abstract: Within a smart city, planning the routes of garbage trucks has to be fast, efficient, and scalable. Optimization of garbage truck routes increases the utilization of the trucks and reduces operational times, costs, and environmental footprint. It may reduce the number of trucks needed to cover the whole city. Faster optimization of routes enables a dynamic real-time update to garbage collection plans. In this paper, mixed integer linear programming is used to automate the route planning optimization problem. It results in an efficient solution within a limited computational time for different operational scenarios.