失效情景下考虑拥堵及偏好的多式联运路径选择

Route selection of multimodal transportation considering congestion and preference under failure scenarios

为保障集装箱运输的经济性,有效规避新冠疫情所造成的风险和损失,助力交通运输业绿色低碳发展,提出失效情景下以多式联运经营人利润最大和运输碳排放总量最小为目标的多目标0-1规划模型。模型不仅考虑节点及路径失效的不确定性,还考虑失效后的拥堵及托运人偏好等影响路径选择的因素。采用蒙特卡洛方法(Monte Carlo method,MCM)结合带精英策略的非支配排序遗传算法(elitist non-dominated sorting genetic algorithm,NSGA-Ⅱ)的混合算法(MCM-NSGA-Ⅱ)对模型进行求解,并以武汉到柏林的集装箱运输为例验证模型及算法的有效性。研究结果表明:托运人偏好、失效及失效后的拥堵会对运输方案的利润、碳排放量、时间产生影响,从而改变帕累托最优运输方案。研究可为制定并优化多式联运方案提供决策支持。

In order to ensure the economy of container transportation,effectively avoid the risks and losses caused by COVID-19,and help the green and low-carbon development of the transportation industry,a multi-objective 0-1 programming model with the maximum profit of multimodal transportation operators and the minimum transport carbon emission as optimization objectives is proposed under failure scenarios.In the model,the uncertainty of node failure and path failure is not only considered,the post-failure congestion,the shipper preference and other factors that affect path selection are but also considered.The Monte Carlo method(MCM)combined with the elitist non-dominated sorting genetic algorithm(NSGA-Ⅱ),called MCM-NSGA-Ⅱ,is used to solve the model.The container transport from Wuhan to Berlin is taken as an example to verify the validity of the model and the algorithm.The results show that,the shipper preference,the failure and the post-failure congestion affect the profit,carbon emission and time of transportation schemes,thus changing the Pareto optimal transportation scheme.The research can provide decision support for making and optimizing the multimodal transportation scheme.