A computational optimization approach to reduce emissions and fuel costs in waste collection services

Effective solid waste management is essential for environmental protection and public health. Municipal Solid Waste (MSW) collection and transportation are crucial components of solid waste management, accounting for up to 80% of total resource allocation. These costs stem from labor expenses, high fuel consumption, and vehicle maintenance. Intensive vehicle usage during these stages leads to substantial energy consumption, atmospheric pollutant emissions, and urban congestion. Route planning offers a promising strategy for reducing costs and emissions associated with waste collection and transportation. Route optimization, also known as the Vehicle Routing Problem (VRP), provides a structured approach to route planning. This study aims to develop a computational model for optimizing waste collection and transportation routes for a small Brazilian municipality, Sapucaia. The proposed optimization problem is addressed using two tools: the Open Source Routing Machine (OSRM) and the Vehicle Routing Open-source Optimization Machine (VROOM). Furthermore, this study includes estimates of greenhouse gas emissions resulting from fuel combustion during waste collection and transportation. For this purpose, a GHG emissions calculation methodology based on the Brazilian GHG Protocol is adopted. The optimization results demonstrate a significant reduction in the total distance traveled. As a consequence of these shorter distances, fuel consumption is also reduced, leading to concomitant decreases in costs and CO2e emissions.