Traffic congestion, road gradients and vehicle load significantly contribute to carbon emissions in urban logistics. However, existing research lacks a comprehensive consideration of these factors. This study introduces and formulates a time-dependent low-carbon vehicle routing problem on road network, which …
This study investigates the collaborative green vehicle routing problem with time-dependent travel speeds (CGVRP-TD), which integrates horizontal collaboration among multiple depots with time-dependent traffic conditions. The problem jointly optimizes customer allocation, vehicle routing, and departure-time decisions to minimize transportation-related carbon …
This study proposes a delay-adaptive neural network (DANN) for querying the TOP-k critical vertices (kCV) on time-dependent shortest paths. Traditional kCV queries are typically formulated on static networks with fixed edge weights, whereas real-world network states often exhibit significant temporal …
This paper deals with the park-and-multi-loop routing problem, in the context of last-mile logistics, in which a fleet of traditional vehicles equipped with several autonomous delivery robots leaves from a depot to service a set of customer requests. Each delivery …
Current urban logistics models often struggle to reconcile diurnal traffic dynamics with rigid spatial–temporal regulations. This decoupling causes “cascading infeasibility,” where traffic delays trigger structural regulatory violations and UAV energy depletion. This study formulates a time-dependent vehicle–UAV joint routing problem …
Timely collection of infectious medical waste (IMW) is essential for reducing the risk of cross-infection under China’s standardized epidemic prevention and control measures. Given the limited duration of protective clothing, medical staff work is divided into shifts, whose duration constitutes …
Real-time navigation systems are increasingly used to provide optimal driving routes together with accurate travel time predictions that reflect dynamic urban traffic conditions. Recent advances have focused on integrating structured traffic data from traditional APIs with unstructured, context-rich information extracted …
Existing truck-drone delivery research often neglects dynamic traffic and inter-route flexibility. To address this, we investigate the Time-Dependent Vehicle Routing Problem with Drones and Inter-route Recovery (TD-VRP-D-IR). We formulate a Mixed-Integer Linear Programming (MILP) model incorporating FIFO-based piecewise speed functions …
The rapid advancement of e-commerce has driven unprecedented expansion in urban logistics networks, where their sustainability is constrained by multifaceted factors including strict time-bound service requirements, employee’s satisfaction, traffic congestion, and carbon emission regulations. Among these critical elements, employee’s satisfaction …
As e-commerce continues to evolve, the issue of first delivery failures due to customers not being at home has become increasingly prominent, significantly increasing the operational costs of logistics companies. This paper considers an incentive-driven (ID) strategy, whereby logistics companies …