不确定条件下的低碳多式联运路径优化研究

Research on Route Optimization of Low Carbon Multimodal Transport Under Uncertainty Condition

在传统的多式联运优化模型中,从承运人角度,考虑实际运输过程中的不确定性和运输方案制定的超前性,引入三角模糊变量表示不确定的货物需求量,并对节点和目的地设置模糊时间窗,以运输成本最小和碳排放费用最小为目标建立优化模型,考虑运输能力、中转能力和客户最低满意度等约束的限制,通过模糊机会约束理论将含有不确定变量的优化模型转化为确定形式的数学模型,采用启发式算法进行求解,并设计案例验证模型的正确性和适用性。结果表明,在承运人优先考虑运输成本和碳排放量时,会更倾向于环境友好型的公铁联运模式;合理预估时间窗,在满足运输能力和中转能力约束的前提下,可以优化路径选择,有助于降低货物运输成本和碳排放量。

In the traditional optimization model of multimodal transport, this paper introduced triangular fuzzy variables to represent the uncertain demand for goods by considering the uncertainty in the actual transportation process and the advance of transportation scheme formulation from the perspective of the carrier, set fuzzy time windows for nodes and destinations, and established the optimization model to minimize transportation and carbon emission costs. In addition,considering the constraints such as transportation and transfer capacity and minimum customer satisfaction, the paper transformed the optimization model with uncertain variables into a mathematical model in a certain form through fuzzy chance-constrained theory, solved the model by heuristic algorithm, and designed a case to verify the correctness and applicability of the model. The results show that when giving priority to transportation costs and carbon emissions, the carrier prefers the environment-friendly road rail intermodal mode. Reasonably estimating the time window will help optimize the route selection to a certain extent on the premise of meeting the constraints of transportation and transfer capacity and reduce freight transportation costs and carbon emissions.