Research On Multimodal Transport Route Optimization And Algorithm Of Refrigerated Container From The Perspective Of Low Carbon

The rapid development of the global economy has led to increasingly serious climate and environmental problems,and countries are gradually establishing a green and low-carbon circular development industrial system to reduce the environmental pressure brought by human activities.China is vigorously promoting green and sustainable development and accelerating the green transformation of various industry development methods,among which,the cold chain logistics industry has the characteristics of high energy consumption and needs to consider economic and environmental benefits.With the increasing demand for cold chain goods,the scale of cold chain logistics transportation has expanded,and the environmental problems caused by long-distance cross-regional cold chain cargo transportation have become more prominent.Research on cross-regional and long-distance multimodal transport of refrigerated containers,and promote cold chain multimodal transport with refrigerated containers as the transportation unit,which can effectively ensure the quality of goods,reduce the loss of goods,and improve the level of cold chain logistics in China.Combining the characteristics of multimodal transport and cold chain logistics transportation,this paper comprehensively considers the transportation cost of transportation routes,the transit cost of the change of transportation mode in node cities,the cargo damage cost related to the shelf life of goods and the decline point of cargo quality,and the refrigeration cost related to transportation time.Path optimization model of multimodal mode of refrigerated container with minimal combined cost such as refrigeration cost and carbon emission cost.In this paper,Particle Swarm Optimization,Genetic Algorithm and Hybrid Particle Swarm Optimization are used to solve the multimodal transport route optimization model of reefer containers.A study of the transportation network of 29 cities is designed to verify it,and the optimal route and transportation mode combination of the three algorithms are analyzed,and the superiority of the Hybrid Particle Swarm Optimization in solving the multimodal transport route optimization problem is demonstrated.Finally,based on the optimal results of the example,the composition of the target cost is analyzed,the sensitivity analysis of carbon tax and the shelf life of fresh agricultural products is carried out,and the influence of carbon tax on route selection and transportation mode combination is explored,and it is concluded that appropriately increasing carbon tax can increase the participation of railway transportation in multimodal transport and effectively reduce carbon emissions.The influence of the shelf life of fresh agricultural products on the choice of route and the combination of transportation modes was discussed,and it was concluded that the longer the shelf life,the transportation of agricultural products changed from time-sensitive public railwater combined transportation to iron-water combined transport.According to the carbon tax and the shelf life of the transported agricultural products,it provides a reference for the transportation route and transportation mode combination of multimodal transport operators.