Research on Railway Transportation Optimization Based on NSGA-Ⅱ Algorithm
Abstract：To improve the efficiency of railway freight transportation and reduce energy consumption, this paper adopts the Non-dominated Sorting Genetic Algorithm with an elite strategy (NSGA-Ⅱ) to establish an optimization model for railway transportation organization, aiming to optimize the railway freight transportation routes. To verify the effectiveness of the model, a case study was designed for optimization experiments. The results show that after optimizing the existing transportation organization using this model, CO2 emissions can be reduced by 0.76 billion tons, and the transportation turnover can be increased by 1,698.46 billion ton-kilometers. Additionally, the sensitivity coefficients are all less than 3.5%, verifying the practicality of the proposed model. The study shows that the model can effectively optimize railway transportation organization and reduce carbon emissions.
Keywords：NSGA-Ⅱ algorithmrailway transportationoptimization modelcarbon emissions
Publication Date：2025-02-27
Pages：3( 26-28 )