With the rapid growth of the economy, container transportation in our country has been flourishing, and the issue of carbon emissions in the collection and distribution process has attracted significant attention. Currently, there are still issues such as unreasonable distribution of cargo flows and uncoordinated proportions of collection and distribution in the development of port collection and distribution in our country. Against this backdrop, an optimization model for collection and distribution is constructed with the goal of minimizing the generalized transportation cost, considering the costs of intransit transportation, transshipment, time, and carbon emissions. The model takes into account constraints on path capacity, transshipment capacity, and transportation demand. A case study is conducted using data from Yangluo Port, and the model is solved using a differential evolution algorithm. The impact of transportation capacity constraints on the optimization scheme is analyzed, leading to the following conclusions: Container port collection and distribution that considers carbon emission costs tends to favor rail transport. Moreover, increasing the capacity of rail and waterway transport in the collection and distribution network can significantly reduce generalized transportation costs and carbon emissions in the process, which is conducive to the development of low-carbon collection and distribution.
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