Multimodal Transportation Route Optimization Under Carbon Tax Policy: Research from Taiyuan University of Technology

Strategic Insights -

New research has shed light on the importance of low-carbon policies in the transportation sector, particularly in regions with different development levels. A study conducted by researchers at Taiyuan University of Technology in China has explored the use of a bi-objective route optimization model to minimize total transportation cost and time while considering uncertain demand, fixed departure schedules, and regional differences. The research findings indicate that the proposed fuzzy adaptive non-dominated sorting genetic algorithm outperforms traditional algorithms in achieving minimum differences in percentages of cost and time.

Key Takeaways:

  • The study explores the use of a bi-objective route optimization model to minimize total transportation cost and time in multimodal transportation systems.
  • The proposed fuzzy adaptive non-dominated sorting genetic algorithm outperforms the NSGA-II algorithm, achieving minimum differences in percentages of cost and time of 9.25% and 7.72%, respectively.
  • The degree of carbon emission reduction varies depending on the development of the regional transportation network, with the eastern region experiencing a higher reduction rate (up to 44.17%) compared to the western region (14.37%).
  • Formulating differentiated carbon tax policies based on local conditions is an effective way to maximize the economic and environmental benefits of multimodal transportation.
  • The research highlights the importance of regional differences in the implementation effect of low-carbon policies and suggests that a tailored approach is necessary for effective carbon emissions reduction.

Statistics:

  • 9.25%: minimum difference in percentage of cost achieved by the proposed fuzzy adaptive non-dominated sorting genetic algorithm compared to the NSGA-II algorithm.
  • 7.72%: minimum difference in percentage of time achieved by the proposed fuzzy adaptive non-dominated sorting genetic algorithm compared to the NSGA-II algorithm.
  • 44.17%: maximum reduction in carbon emissions in the eastern region as the carbon tax rate increases.
  • 14.37%: maximum reduction in carbon emissions in the western region as the carbon tax rate increases.

Sources:

  • Route Optimization of Multimodal Transport Considering Regional Differences Under Carbon Tax Policy. Sustainability, 2025;17(13):5743.
  • Taiyuan University of Technology, School of Economics and Management, Taiyuan 030000, People's Republic of China.
  • National Natural Science Foundation of China.