低碳背景下的多式联运路径规划

低碳运输一直是世界各国关注的焦点，多式联运作为一种主要的运输组织形式，国内外的文献中却少有关于多式联运碳排放研究的文章.本文提出了运输总成本最小和运输碳排放总量最小的多目标0-1规划模型，构建运输总成本时不仅考虑了运输弧段上的运输成本、运输节点的换装成本、铁路车站及水运码头的存储成本还考虑了运输弧段与代理商的匹配关系.运输碳排放量则由运输过程碳排放和换装过程的碳排放构成.采用改进的带精英策略的非支配排序遗传算法(NSGA-II)对模型进行求解，算法能有效保存优秀个体和降低计算的复杂度.最后通过算例验证了模型和算法有效性.

Multimodal Transportation Route Planning under Low Carbon Emissions Background

Low-carbon transportation is the focus of attention of countries around the world. The multimodal transportation is a major form of transport organization. However, there is a little literature aims at researching multimodal transportation' s carbon emissions at home and abroad. The paper proposes a multi-objective 0-1 programming model for minimizing the total transportation cost and minimizing the total amount of transportation carbon emissions. The transportation cost on the arcs, reloading cost at the transport node, the storage cost at railway station and in the port, the matching relationship between the transport arcs and the agents are all considered when constructing the total transportation cost. the total multimodal transportation' s carbon emissions consists of carbon emissions from transport processes and reloading processes. An improved elitist strategy nondominated sorting genetic algorithm (NSGA-II) is used to solve the model. The algorithm can save the outstanding individuals and reduce the computational complexity effectively. Finally, an example is given to demonstrate the effectiveness of the model and algorithm.