Research On Optimization Of Container Low-carbon Multimodal Transport Path Under Uncertain Demand

Container multimodal transportation is the key to improving transportation efficiency and promoting the development of my country’s transportation.It is also a sharp edge to reduce costs and improve my country’s economic competitiveness.How to optimize container transportation routes under the internal and external conditions of carbon emission reduction policies and dynamic demand changes is a key issue for the development of container multimodal transport.Therefore,in the case of uncertain market demand,reasonable optimization of container low-carbon multimodal transportation routes has important theoretical and practical significance for reducing carbon emissions,reducing costs,and effectively achieving a win-win economic benefit and environmental protection.Based on this,this article has done the following work:First,describe the research background and sence of this article,analyze the relevant domestic and foreign literature,propose the research content and research methods of this article,and relate to container multimodal transportation,low-carbon multimodal transportation,robust optimization methods,and genetic algorithms.The theory is explained to lay a good theoretical foundation for the follow-up research.Secondly,it summarizes the optimization of container low-carbon multimodal transportation route,proposes the optimization subject and elaborates on the cost composition.Thirdly,with the goal of minimizing the total cost,a low-carbon multimodal transportation route optimization model for containers under demand determination and demand uncertainty is established respectively,and a Monte Carlo-based catastrophe adaptive genetic algorithm is proposed to solve the model.Finally,apply the model to an example to verify the effectiveness of the improved algorithm by comparing the traditional genetic algorithm with the improved genetic algorithm;compare the results under demand determination and demand uncertainty to verify the robust optimization characteristics of the model;adjust the carbon tax rate,Carry out the corresponding sensitivity analysis.This article aims to solve the problem of container low-carbon multimodal transportation route optimization in a relatively stable way under uncertain demand,taking into account container transportation costs,transshipment costs,time costs,and carbon emission costs based on segmented progressive carbon tax rates.The pursuit of minimizing the total cost of the system,while using robustness to reduce system instability.This can not only reduce logistics costs,reduce environmental burdens,achievea win-win situation for multiple parties,but also ensure the stable operation of the multimodal transport system,effectively meet the needs of low-carbon,dynamic,and personalized transportation,and promote the scientific development of the transportation industry.