| description abstract | The sustainability of transportation networks is threatened by growing amounts of emissions generated by vehicles. Urban freight delivery is one of the major sources of these emissions. Cargo cycles are attracting increasing attention for urban delivery owing to their numerous benefits, such as being less pollutant, requiring less space on roads, and high maneuverability. Electric vans have also been proposed as another green mode of freight delivery with a larger delivery capacity and range relative to cargo cycles. In this study, urban freight delivery is targeted through a heterogeneous fleet vehicle routing problem. The proposed framework is used to capture the optimal configuration of a mixed freight delivery fleet offering cargo cycles (i.e., pedal-assisted bikes and trikes as well as electric bikes and trikes) alongside the often-used diesel or gasoline vans or small trucks and electric vans. The formulated problem aims to minimize the delivery costs for companies, including maintenance, purchase, fuel, and labor costs and noise and emission taxes. The methodological contribution of this study is to develop a new metaheuristic algorithm, based on variable neighborhood search and simulated annealing, that finds a better solution with up to 7% lower objective function value and 50% to 80% lower solution times relative to the existing approaches in the literature. This study also demonstrates that bikes and trikes are selected at short delivery distances in the Chicago downtown network. Electric vans are more suitable for large distances, while cargo vans are selected for medium distances. Imposing an emission tax would change the model from cargo vans to electric vans. The results also show that increasing tax levels does not necessarily reduce societal costs because the delivery company tends to maintain its profit margin by increasing delivery costs for customers. | |
