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Optimization Of Headway, Vehicle Size and Route Choice for Minimum Cost Feeder Service

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  • Steven I-JY Chien

Abstract

Many people use public transportation systems to reach their destination, while others use personal vehicles. Poor transportation systems do not attract ridership. Therefore, the usage of passenger cars increases, and traffic and environmental conditions deteriorate. Efficient public transportation has been recognized as one of the potential ways of mitigating air pollution, reducing energy consumption, improving mobility and alleviating traffic congestion. The objective of this study is to optimize a bus feeder service that provides the shuttle service between a recreation center (e.g. Sandy Hook, NJ) and a major public transportation facility, subject to site-specific constraints such as vehicle schedules, bus availability, service capacity and budget. The decision variables include bus headway, vehicle size and route choice. The solution methodology integrating both analytical and numerical techniques is developed, which optimizes the decision variables. Finally, the proposed solution methodology is applied to a case study. Numerical results, including optimal solutions and sensitivity analyses, are presented while the level of coordination between the feeder service and a major transportation service is discussed.

Suggested Citation

  • Steven I-JY Chien, 2005. "Optimization Of Headway, Vehicle Size and Route Choice for Minimum Cost Feeder Service," Transportation Planning and Technology, Taylor & Francis Journals, vol. 28(5), pages 359-380, August.
  • Handle: RePEc:taf:transp:v:28:y:2005:i:5:p:359-380
    DOI: 10.1080/03081060500322565
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    Cited by:

    1. Liang, Jinpeng & Wu, Jianjun & Qu, Yunchao & Yin, Haodong & Qu, Xiaobo & Gao, Ziyou, 2019. "Robust bus bridging service design under rail transit system disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 132(C), pages 97-116.
    2. Wang, Po-Chieh & Hsu, Yu-Ting & Hsu, Chia-Wei, 2021. "Analysis of waiting time perception of bus passengers provided with mobile service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 319-336.
    3. Liang, Jinpeng & Wu, Jianjun & Gao, Ziyou & Sun, Huijun & Yang, Xin & Lo, Hong K., 2019. "Bus transit network design with uncertainties on the basis of a metro network: A two-step model framework," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 115-138.
    4. Sergei Dytckov & Jan A. Persson & Fabian Lorig & Paul Davidsson, 2022. "Potential Benefits of Demand Responsive Transport in Rural Areas: A Simulation Study in Lolland, Denmark," Sustainability, MDPI, vol. 14(6), pages 1-21, March.
    5. Islam, Md. Kamrul & Vandenbona, Upali & Dixit, Vinayak V. & Sharma, Ashish, 2015. "A Simplified Method for Performance Evaluation of Public Transit Under Reneging Behavior of Passengers," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 54(3).
    6. Hatzenbühler, Jonas & Cats, Oded & Jenelius, Erik, 2020. "Transitioning towards the deployment of line-based autonomous buses: Consequences for service frequency and vehicle capacity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 491-507.
    7. Park, Chung & Lee, Jungpyo & Sohn, So Young, 2019. "Recommendation of feeder bus routes using neural network embedding-based optimization," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 329-341.
    8. Mohammad Hadi Almasi & Ali Sadollah & Seungmo Kang & Mohamed Rehan Karim, 2016. "Optimization of an Improved Intermodal Transit Model Equipped with Feeder Bus and Railway Systems Using Metaheuristics Approaches," Sustainability, MDPI, vol. 8(6), pages 1-27, June.
    9. Sigler, Devon & Wang, Qichao & Liu, Zhaocai & Garikapati, Venu & Kotz, Andrew & Kelly, Kenneth J. & Lunacek, Monte & Phillips, Caleb, 2021. "Route optimization for energy efficient airport shuttle operations – A case study from Dallas Fort worth International Airport," Journal of Air Transport Management, Elsevier, vol. 94(C).
    10. Ruiz, Elkin & Yushimito, Wilfredo F. & Aburto, Luis & de la Cruz, Rolando, 2024. "Predicting passenger satisfaction in public transportation using machine learning models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).

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