Research On Decision-Making Of Railway Participation In Multimodal Transport Under The Perspective Of Low Carbon

Multimodal transport is a composite transport mode formed by the interconnection and transshipment of two or more modes of transportation,such as road and rail.Multimodal transport can not only greatly improve the efficiency of goods circulation,but also effectively reduce carbon emissions,thus achieving efficient,safe and high-quality transportation of goods.As the world becomes more and more concerned about environmental protection,governments are taking more active measures to reduce carbon emissions,such as implementing carbon trading,carbon taxation,and mandatory carbon emission restrictions.Under the background and environment of national policies such as "public to railway" and "carbon neutral and carbon peak",railroads have become a key factor to achieve "double carbon".Under the background and environment of "double carbon" and "carbon neutral,carbon peak" policies,railways have become the main transportation mode and an important measure to achieve "double carbon",transportation timeliness and economy.Therefore,this study aims to focus on container multimodal transport decision making and its transport coordination and management from the perspective of low carbon,further study the optimization of transport routes and transport modes to achieve the best economic benefits,and provide an important reference basis for the decision management,transport organization and participants of railroad participation in multimodal transport system.For the multimodal transport path planning problem with fuzzy demand and fuzzy time under different carbon emission policies,the optimization model of railroad participation in multimodal transport path under different low-carbon policies is constructed with the cost and time of multimodal transport under low carbon emission as the target.For the multimodal transport path decision problem under different low-carbon policies,many uncertainties in the environment and the influence of transport and transit capacity of the road sections and each node on the path decision are considered to study a more economical and low-carbon transport decision.The improved Sparrow Search Algorithm(SSA)is used to construct the optimal multimodal transport path model,and the number of iterations is used as the degree of freedom of t-distribution,which effectively balances the ability of local search and global search,thus overcoming the defect that SSA is easy to fall into local optimality and realizing the optimal transport path for railroad participation in multimodal transport under low-carbon perspective selection.The experimental results show that mandatory carbon emission and carbon tax policies can effectively reduce carbon emissions.For the evaluation of optimal route selection,a comprehensive evaluation method based on the combination of sequential relationship method,entropy power fuzzy hierarchy analysis method and combined assignment method is used to establish an evaluation system with transportation time,transportation cost,carbon emission and comprehensive energy consumption as evaluation indexes to achieve the final comprehensive evaluation of the effect of optimal route selection,taking into account the characteristics of railroad participation in multimodal transportation and the efficiency characteristics of multimodal transportation.The final comprehensive evaluation of the effect of optimal route selection is achieved.Finally,taking Shanghai-Hamburg transport network structure as an example,different transport routes and hub nodes are selected,and the optimal transport path of Shanghai-Hamburg transport network is obtained by using the constructed model of railroad participation in multimodal transport path optimization under different low-carbon policies,with the objective of multimodal transport cost and time under low carbon emission.Further,the designed comprehensive evaluation method is used to achieve the final comprehensive evaluation of the optimal route selection effect based on multiple indicators such as transportation time,transportation cost and carbon emission.