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Multiobjective-Based Decision-Making for the Optimization of an Urban Passenger Traffic System Structure

Author

Listed:
  • Wenhui Zhang

    (School of Civil Engineering and Transportation, Northeast Forestry University, Harbin 150040, China)

  • Yajing Song

    (School of Civil Engineering and Transportation, Northeast Forestry University, Harbin 150040, China)

  • Ge Zhou

    (School of Civil Engineering and Transportation, Northeast Forestry University, Harbin 150040, China)

  • Ziwen Song

    (School of Civil Engineering and Transportation, Northeast Forestry University, Harbin 150040, China)

  • Cong Xi

    (School of Civil Engineering and Transportation, Northeast Forestry University, Harbin 150040, China)

Abstract

Urbanization has aggravated the conflict between continuously increasing urban travel demands and limited supply. Moreover, the inability to expand urban roads due to previous land planning and utilization has resulted in significant traffic congestion, traffic safety issues, and environmental problems. To address these problems, this work attempted to develop a multiobjective model to optimize the passenger traffic system while considering carbon emissions, transport costs, and resource utilization. In addition, the ideal point method and entropy weight method were combined to obtain the optimal solution. Based on the operational data on traffic modes and travel data on passengers in Harbin, the northern capital of China, the proposed method was used to solve the case in Harbin. The results show that the proportion of buses increased by 1.05%, that of subways increased by 36.60%, that of taxis decreased by 11.86%, and that of private cars decreased by 25.78% after optimization. Furthermore, the analyses of the results show that the optimized passenger traffic system structure can promote the sustainable development of urban transport and demonstrate the practicality of the proposed method for solving multiobjective optimization problems. Relative to the ideal point method and genetic algorithm, the proposed method is more applicable for optimizing the passenger traffic structure in Harbin. In addition, this study explored the sensitivity of the optimization goals to the four motorized modes. The results show that subways and private cars are the key areas to prioritize in adjusting the urban passenger traffic system structure. Based on the analysis results, recommendations for the development of transportation in Harbin are given. This study provides a reference for decision-makers to formulate policies for the urban sustainable development of Harbin as well as for transportation development in other cities.

Suggested Citation

  • Wenhui Zhang & Yajing Song & Ge Zhou & Ziwen Song & Cong Xi, 2023. "Multiobjective-Based Decision-Making for the Optimization of an Urban Passenger Traffic System Structure," Sustainability, MDPI, vol. 15(18), pages 1-20, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13644-:d:1238411
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    References listed on IDEAS

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    1. Ali Louati & Elham Kariri, 2023. "Enhancing Intersection Performance for Tram and Connected Vehicles through a Collaborative Optimization," Sustainability, MDPI, vol. 15(12), pages 1-17, June.
    2. Qu, Kaiping & Yu, Tao & Zhang, Xiaoshun & Li, Haofei, 2019. "Homogenized adjacent points method: A novel Pareto optimizer for linearized multi-objective optimal energy flow of integrated electricity and gas system," Applied Energy, Elsevier, vol. 233, pages 338-351.
    3. Matteo Mazziotta & Adriano Pareto, 2022. "Normalization methods for spatio‐temporal analysis of environmental performance: Revisiting the Min–Max method," Environmetrics, John Wiley & Sons, Ltd., vol. 33(5), August.
    4. Leng, Jun-qiang & Zhai, Jing & Li, Qian-wen & Zhao, Lin, 2018. "Construction of road network vulnerability evaluation index based on general travel cost," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 421-429.
    5. Wang, Shaojian & Liu, Xiaoping & Zhou, Chunshan & Hu, Jincan & Ou, Jinpei, 2017. "Examining the impacts of socioeconomic factors, urban form, and transportation networks on CO2 emissions in China’s megacities," Applied Energy, Elsevier, vol. 185(P1), pages 189-200.
    6. Zhang, Linling & Long, Ruyin & Li, Wenbo & Wei, Jia, 2020. "Potential for reducing carbon emissions from urban traffic based on the carbon emission satisfaction: Case study in Shanghai," Journal of Transport Geography, Elsevier, vol. 85(C).
    7. Kang, Sanghoon, 2016. "Associations between space–time constraints and spatial patterns of travels," Annals of Tourism Research, Elsevier, vol. 61(C), pages 127-141.
    8. Rui Ding & Yilin Zhang & Ting Zhang & Can Ma & Jiaojiao Jiang, 2021. "Development of a Complex Network-Based Integrated Multilayer Urban Growth and Optimisation Model for an Efficient Urban Traffic Network," Complexity, Hindawi, vol. 2021, pages 1-16, January.
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    2. Xinhua Gao & Song Liu & Shan Jiang & Dennis Yu & Yong Peng & Xianting Ma & Wenting Lin, 2024. "Optimizing the Three-Dimensional Multi-Objective of Feeder Bus Routes Considering the Timetable," Mathematics, MDPI, vol. 12(7), pages 1-27, March.

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