Research On Optimization Of Multimodal Transport Path Considering Carbon Emissions In Uncertain Condition

With the acceleration of the development process of international logistics,container multimodal transport is also widely used.Although multimodal transport combines various modes of transport,making the transport process more flexible and environmentally friendly,it is affected by time,transport volume and other factors,so that it has a high degree of uncertainty.In addition,the transport sector is responsible for 22% of carbon emissions,making it imperative to save energy and reduce emissions.Therefore,the research on optimization of multimodal transport path considering carbon emissions in uncertain conditions can not only discuss the formulation of lowcarbon policies in the transport industry,but also help promote the optimization of China’s transport structure and provide reference for efficient and green multimodal transport.The main work and achievements of this research are as follows:(1)The low-carbon policy game model of freight transport industry is studied.Considering that the government,transportation enterprises and even shippers have different carbon emission reduction responsibilities,a two-stage Stackelberg game method is adopted.The first phase of the game between the government and enterprises through simulation,the government to transport enterprises and shippers the optimal proportion law of carbon tariffs,the second stage studies only for a carbon tax of transport enterprises,a hybrid carbon tax on transport enterprises and shippers,only to shippers these three carbon tax levy a carbon tax policy under the transport enterprises,such as the optimal traffic and carbon emissions optimal decision.(2)In this study,the optimization of multimodal transportation path considering carbon emission in uncertain conditions is studied.Combined with transportation cost,transportation cost and time cost,the uncertain conditions are analyzed and the fuzzy processing is carried out to establish a stable optimization model under uncertain conditions.According to the development requirements of low carbon and environmental protection,combined with the operating mechanism of carbon tax policy,carbon cap policy,carbon cap and trade policy and carbon offset policy,the models are respectively converted into the corresponding carbon cost or carbon constraint to establish a complete optimization model.(3)The path optimization model considering four carbon emission policies under uncertain conditions is solved.First design based on the Monte Carlo catastrophe adaptive genetic algorithm,and then in Wuhan-Hamburg’s container multimodal transport as an example,combined with the second chapter game to get the optimal tax and optimal volume and optimal carbon emissions data,collect related data,to the path optimization model,using the improved optimization algorithm for solving,to verify the effectiveness of the algorithm.Finally,sensitivity analysis is conducted on time,demand and four carbon emission policies.In this study,the application of Stackelberg game method in transportation industry is extended to some extent,and the optimization model under stable uncertain conditions is established,which has a certain reference for the optimization of multimodal transportation path.