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Optimization of the Waterbus Operation Plan Considering Carbon Emissions: The Case of Zhoushan City

Author

Listed:
  • Juying Wang

    (School of Management, Ocean University of China, Qingdao City 266100, China)

  • Feng Guan

    (Transportation Management College, Dalian Maritime University, Dalian 116026, China)

  • Ting Li

    (Transportation Management College, Dalian Maritime University, Dalian 116026, China)

  • Can Wang

    (Transportation Management College, Dalian Maritime University, Dalian 116026, China)

  • Qianqian Han

    (School of Accountancy, Shandong University of Finance and Economics, Jinan 250014, China)

  • Bin Yu

    (Transportation Management College, Dalian Maritime University, Dalian 116026, China)

Abstract

Recently, as more people are concerned with the issues around environment protection, research about how to reduce carbon emissions has drawn increasing attention. Encouraging public transportation is an effective measure to reduce carbon emissions. However, overland public transportation does less to lower carbon because of the gradually increasing pressure of the urban road traffic. Therefore, the waterbus along the coast becomes a new direction of the urban public transport development. In order to optimize the operation plan of the waterbus, a bi-level model considering carbon emissions is proposed in this paper. In the upper-level model, a multiple objective model is established, which considers both the interests of the passengers and the operator while considering the carbon emissions. The lower-level model is a traffic model split by using a Nested Logit model. A NSGA-II (Non-dominated Sorting Genetic Algorithm-II) algorithm is proposed to solve the model. Finally, the city of Zhoushan is chosen as an example to prove the feasibility of the model and the algorithm. The result shows that the proposed model for waterbus operation optimization can efficiently reduce transportation carbon emissions and satisfy passenger demand at the same time.

Suggested Citation

  • Juying Wang & Feng Guan & Ting Li & Can Wang & Qianqian Han & Bin Yu, 2015. "Optimization of the Waterbus Operation Plan Considering Carbon Emissions: The Case of Zhoushan City," Sustainability, MDPI, vol. 7(8), pages 1-18, August.
  • Handle: RePEc:gam:jsusta:v:7:y:2015:i:8:p:10976-10993:d:54039
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    References listed on IDEAS

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    1. Malte Meinshausen & S. Smith & K. Calvin & J. Daniel & M. Kainuma & J-F. Lamarque & K. Matsumoto & S. Montzka & S. Raper & K. Riahi & A. Thomson & G. Velders & D.P. Vuuren, 2011. "The RCP greenhouse gas concentrations and their extensions from 1765 to 2300," Climatic Change, Springer, vol. 109(1), pages 213-241, November.
    2. Ennio Cascetta, 2009. "Transportation Systems Analysis," Springer Optimization and Its Applications, Springer, number 978-0-387-75857-2, June.
    3. Wen, Chieh-Hua & Koppelman, Frank S., 2001. "The generalized nested logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 627-641, August.
    4. Jean-François Cordeau & Paolo Toth & Daniele Vigo, 1998. "A Survey of Optimization Models for Train Routing and Scheduling," Transportation Science, INFORMS, vol. 32(4), pages 380-404, November.
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    Cited by:

    1. Shiqi Li & Maoxiang Lang & Xueqiao Yu & Mingyue Zhang & Minghe Jiang & Sangbing Tsai & Cheng-Kuang Wang & Fang Bian, 2019. "A Sustainable Transport Competitiveness Analysis of the China Railway Express in the Context of the Belt and Road Initiative," Sustainability, MDPI, vol. 11(10), pages 1-30, May.

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