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Many-objective optimization of multi-mode public transportation under carbon emission reduction

Author

Listed:
  • Zhao, Chuyun
  • Tang, Jinjun
  • Gao, Wenyuan
  • Zeng, Yu
  • Li, Zhitao

Abstract

The incoordination between public transportation system construction and urban infrastructure development is a challenge for the sustainable development of cities. Exploring the associations between the built environment, transportation, and carbon emissions from a macro perspective is significant for realizing the goal of low-carbon urban transportation. This study proposes a collaborative optimization framework for the built environment and public transportation structure under carbon emission reduction. The purpose is to enhance the services capacity and emission reduction potential of public transportation with limited resources. Six factors are considered to construct the many-objective optimization model, including carbon emissions, energy consumption, government subsidies, time and economic costs, and road network resource occupation. The parameters of the model are calculated based on various multi-mode travel data (including vehicle order data, vehicle global positioning system (GPS) trajectory data, and intelligent card (IC) data) and built environment data. During the process, a data processing method for identifying bus drop-off points and inferring urban functional areas is developed. Then, the NSGA–III–DE (Differential Evolution) algorithm is designed to obtain the optimal solutions. The methodological framework is validated in the experiment implemented in Shenzhen city. According to the hypervolume (HV) value, the performance of NSGA–III–DE is compared with that of NSGA-II and NSGA-III. The results show that NSGA–III–DE has better global search ability and presents stable performance for different mutation operators. Finally, the optimization results are further discussed to provide effective guidance for urban planning and low-carbon transportation.

Suggested Citation

  • Zhao, Chuyun & Tang, Jinjun & Gao, Wenyuan & Zeng, Yu & Li, Zhitao, 2024. "Many-objective optimization of multi-mode public transportation under carbon emission reduction," Energy, Elsevier, vol. 286(C).
  • Handle: RePEc:eee:energy:v:286:y:2024:i:c:s0360544223030219
    DOI: 10.1016/j.energy.2023.129627
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    References listed on IDEAS

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    1. Chen, Fangxi & Yin, Zhiwei & Ye, Yingwei & Sun, Daniel(Jian), 2020. "Taxi hailing choice behavior and economic benefit analysis of emission reduction based on multi-mode travel big data," Transport Policy, Elsevier, vol. 97(C), pages 73-84.
    2. Arvin, Mak B. & Pradhan, Rudra P. & Norman, Neville R., 2015. "Transportation intensity, urbanization, economic growth, and CO2 emissions in the G-20 countries," Utilities Policy, Elsevier, vol. 35(C), pages 50-66.
    3. Shuling Chen & Jianhong Wu & Yueqi Zong, 2020. "The Impact of the Freight Transport Modal Shift Policy on China’s Carbon Emissions Reduction," Sustainability, MDPI, vol. 12(2), pages 1-21, January.
    4. Xue, Fei & Yao, Enjian, 2022. "Impact analysis of residential relocation on ownership, usage, and carbon-dioxide emissions of private cars," Energy, Elsevier, vol. 252(C).
    5. Liu, Xiaoping & Ou, Jinpei & Chen, Yimin & Wang, Shaojian & Li, Xia & Jiao, Limin & Liu, Yaolin, 2019. "Scenario simulation of urban energy-related CO2 emissions by coupling the socioeconomic factors and spatial structures," Applied Energy, Elsevier, vol. 238(C), pages 1163-1178.
    6. Anderson, John E. & Wulfhorst, Gebhard & Lang, Werner, 2015. "Energy analysis of the built environment—A review and outlook," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 149-158.
    7. Wusheng Liu & Qian Tan & Lisheng Liu, 2020. "Destination Estimation for Bus Passengers Based on Data Fusion," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-10, September.
    8. Cui, Qiang & Li, Ye, 2015. "An empirical study on the influencing factors of transportation carbon efficiency: Evidences from fifteen countries," Applied Energy, Elsevier, vol. 141(C), pages 209-217.
    9. Song, Siqi & Diao, Mi & Feng, Chen-Chieh, 2016. "Individual transport emissions and the built environment: A structural equation modelling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 206-219.
    10. Wenyue Yang & Shaojian Wang & Xiaoming Zhao, 2018. "Measuring the Direct and Indirect Effects of Neighborhood-Built Environments on Travel-related CO 2 Emissions: A Structural Equation Modeling Approach," Sustainability, MDPI, vol. 10(5), pages 1-14, April.
    11. Heres-Del-Valle, David & Niemeier, Deb, 2011. "CO2 emissions: Are land-use changes enough for California to reduce VMT? Specification of a two-part model with instrumental variables," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 150-161, January.
    12. Tan Yigitcanlar & Fatih Dur, 2010. "Developing a Sustainability Assessment Model: The Sustainable Infrastructure, Land-Use, Environment and Transport Model," Sustainability, MDPI, vol. 2(1), pages 1-20, January.
    13. Choi, Kwangyul & Zhang, Ming, 2017. "The impact of metropolitan, county, and local land use on driving emissions in US metropolitan areas: Mediator effects of vehicle travel characteristics," Journal of Transport Geography, Elsevier, vol. 64(C), pages 195-202.
    14. Solaymani, Saeed, 2019. "CO2 emissions patterns in 7 top carbon emitter economies: The case of transport sector," Energy, Elsevier, vol. 168(C), pages 989-1001.
    15. Du, Huibin & Li, Qun & Liu, Xi & Peng, Binbin & Southworth, Frank, 2021. "Costs and potentials of reducing CO2 emissions in China's transport sector: Findings from an energy system analysis," Energy, Elsevier, vol. 234(C).
    16. Yunqiang Xue & Hongzhi Guan & Jonathan Corey & Bing Zhang & Hai Yan & Yan Han & Huanmei Qin, 2017. "Transport Emissions and Energy Consumption Impacts of Private Capital Investment in Public Transport," Sustainability, MDPI, vol. 9(10), pages 1-19, October.
    17. Zhong, Shaopeng & Bushell, Max, 2017. "Impact of the built environment on the vehicle emission effects of road pricing policies: A simulation case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 235-249.
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