Optimisation of the Dynamic Waste Collection

The aim of this work is to show how to optimise Waste Collection (WC) services in the context of the use of the Internet of Things (IoT). It is a challenge compared to traditional approaches, which use fixed route planning and imply an unnecessary use of resources by including containers whose fill level does not require emptying on the routes. As part of a Smart Tourism Destination project, Adeje Municipality (Tenerife Island) has chosen to implement IoT smart sensors in waste bins to help address these challenges. The present study proposes the application of the Greedy Randomised Adaptive Search Procedure (GRASP) metaheuristic for dynamic route planning from real-time data. The origin-destination time and distance matrices are obtained using Geographic Information Systems (GIS). A Capacitated Team Orienteering Problem (CTOP) model that maximises the filling of collected containers was used to select the routes. The solutions to the problems are sets of routes for the fleet of trucks that collect waste, taking into account the limitations of the capacity of the truck and the duration of the routes. In this way, overflows are avoided, thus reducing pollution which contributes to the better perception of citizens and tourists.