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Topology Optimization Methods Enhance the Efficiency and Service Quality of Urban Public Transportation Networks

In: Proceedings of the 2025 3rd International Conference on Digital Economy and Management Science (CDEMS 2025)

Author

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  • Chengchen Guo

    (Xuchang University)

Abstract

With the acceleration of urbanization, urban public transportation networks are facing growing travel demands and complex and changing traffic environments. Improving their efficiency and service quality has become an important topic in current urban transportation planning and management. First, this paper introduces the background and research significance of urban public transportation network optimization, and clarifies the importance and urgency of the research. Secondly, by reviewing the research results in related fields, a solid theoretical basis is provided for the research of this paper. Then, the theoretical basis of topology optimization and the construction method of the topological model of urban public transportation network are elaborated in detail. Subsequently, this research validates the efficacy of the topological optimization approach via experiments and conducts an in - depth discussion on the experimental outcomes. The findings indicate that upon the adoption of the topological optimization method, the operational efficiency and service quality of the urban public transportation network have been notably enhanced, with the overall node connectivity data remaining stably above 83%. This shows that the topological optimization method significantly improves the node connectivity of the urban public transportation network, effectively enhances the coverage and accessibility of the network, makes the line layout more reasonable, and significantly improves the travel experience of citizens.

Suggested Citation

  • Chengchen Guo, 2025. "Topology Optimization Methods Enhance the Efficiency and Service Quality of Urban Public Transportation Networks," Advances in Economics, Business and Management Research, in: Wenke Zang & Chunping Xia (ed.), Proceedings of the 2025 3rd International Conference on Digital Economy and Management Science (CDEMS 2025), pages 268-277, Springer.
  • Handle: RePEc:spr:advbcp:978-94-6463-770-0_32
    DOI: 10.2991/978-94-6463-770-0_32
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