Route Optimization on Low-Carbon Multimodal Transport of Refrigerated Containers under Uncertain Demand
The route optimization of multimodal transport of refrigerated containers plays an important role in helping achieve cost reduction and efficiency improvement in the transport of fresh agricultural products.Based on the existing studies,this paper first considered the influence of uncertain demand and carbon emissions and built a route optimization model with the triangular fuzzy number introduced to represent uncertain transport demand,whose goal is to reach the minimum generalized logistics cost.Then,this paper adopted the fuzzy chance constrained programming theory to clarify the model and linearized the nonlinear terms.Finally,the paper applied COPT7.0 solver to solve the model and conducted the case solution and the comparative analysis,as well as the sensitivity analysis of carbon tax rates and confidence level.The results show that the multimodal transport of refrigerated containers can reduce the cost of transporting fresh agricultural products and improve its efficiency.Reasonably raising carbon tax rates can effectively promote a shift in the shipping method from by road to by rail,which contributes to low-carbon transport.The enhancement in confidence level is conducive to meeting customer demand.Nevertheless,it meanwhile results in a nonlinear increase in the total transport cost since it always involves an adjustment of the transport scheme,due to the limited transport and transit capacity.
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