The swift growth of e-commerce has intensified the pressure on the express delivery industry in terms of timely delivery. Therefore, it becomes imperative to explore the implementation of a joint distribution model that enables more efficient and sustainable delivery of express shipments. Considering factors such as the capacity of delivery stations and the number of transport vehicles, this study proposes a two-level delivery location selection model under the joint distribution mode, aiming to minimize the total cost and carbon emissions of the delivery station location selection. The proposed model is solved using the Improved Multi-objective Particle Swarm Optimization (IMOPSO) algorithm. According to the research results, by adopting the joint distribution model, the total cost can be significantly reduced to 63,867.05 yuan while also achieving a substantial reduction in carbon emissions to 997,945.81 kg. Furthermore, the facility utilization rate exceeds 90%. Notably, the IMOPSO algorithm exhibits notable advantages in terms of both accuracy and computational efficiency.
To achieve carbon peaking and carbon neutrality goals under the new development philosophy, environmentally friendly autonomous driving has become one of the focuses of the automobile industry. It is essential to optimize the fuel consumption in the modeling studies conducted on the trajectories of autonomous vehicles. Moving bottlenecks caused by low-speed vehicles may influence traffic efficiency and generate extra fuel consumption. The emergence of connected self-driving technology makes communications among vehicles and better trajectory control possible. This paper investigates the effects of cooperative adaptive cruise control on fuel consumption under a moving bottleneck. The moving bottleneck is caused by the overtaking of trucks on a two-lane expressway. Our analysis results indicate that cooperative adaptive cruise control can efficiently reduce fuel consumption under the moving bottleneck compared with Gipps’ carfollowing model. Also, the optimization efficiency of cooperative adaptive cruise control increases as the control distance decreases and the initial speed increases.
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