Research on vehicle routing problem with time window and 3D loading constraint considering carbon emission costs

In this work, we address the Vehicle Routing Problem with Time Window and 3D Loading Constraint considering Carbon Emission costs (VRTWLPCE). Our objective is to optimize logistics plans by simultaneously achieving delivery tasks, minimizing carbon emissions, and ensuring feasible loading plans. To achieve this, we propose a hybrid algorithm (HA) which combines various meta-heuristics and local search techniques. Through experiments conducted on 12 benchmark instances, we demonstrate that the HA performs effectively and achieves significant reductions in carbon emission costs. Additionally, we compare carbon emissions under two target modes and observe a downward trend as vehicle usage costs increase.