Abstract
Environmental protection and intelligence have become the inevitable development trend of future transportation. Connected and automated vehicles (CAVs) are expected to be applied in the near future. In this context, how to schedule CAVs to meet customer demands with carbon emissions minimization has become a new green vehicle routing problem (VRP). Due to the fact that carbon emissions are tremendously influenced by vehicle speed, this paper considers vehicle speed as a decision variable in the above low-carbon VRP for CAVs. In addition, the differentiation on speed limits in each time period and each type of road are also taken into account. This study formulates a nonlinear mixed-integer programming model for this problem. The outer-approximate method is used to linearize the proposed model. Moreover, a hybrid particle swarm optimization (HPSO) algorithm is developed to solve this problem. Extensive numerical experiments are conducted to validate the effectiveness of the proposed model and the efficiency of the proposed solution method. Some implications are also drawn out for reducing carbon emissions in logistics activities.
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