Optimizing Sustainable City Logistics: A Time Window and CO2Emissions-Aware Vehicle Routing Approach

Modern digital businesses rely on efficient city logistics to satisfy customers' demands for fast deliveries. However, urban traffic congestion causes delays and significant carbon emissions, contributing to global warming. It is worth noting that vehicle emissions arise not only during transportation (hot emissions) but also during unloading (idle emissions). This research proposes a vehicle routing model for city logistics, aiming to minimize both hot and idle emissions while ensuring timely deliveries and meeting customer demands. The model considers traffic variations, and a heuristic algorithm is introduced to solve benchmark problems with 100 nodes. The algorithm's effectiveness is evaluated, and its solutions are compared to those generated by a traditional VRP algorithm that minimizes total distance and travel time. The results show that the proposed algorithm outperforms the traditional approach in terms of environmental and economic considerations.