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Optimization of a feeder-bus route design by using a multiobjective programming approach

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  • Jen-Jia Lin
  • Huei-In Wong

Abstract

This paper presents a feeder-bus route design model, capable of minimizing route length, minimizing maximum route travel time of planned routes, and maximizing service coverage for trip generation. The proposed model considers constraints of route connectivity, subtour prevention, travel time upper bound of a route, relationships between route layout and service coverage, and value ranges of decision variables. Parameter uncertainties are dealt with using fuzzy numbers, and the model is developed as a multiobjective programming problem. A case study of a metro station in Taichung City, Taiwan is then conducted. Next, the programming problem in the case study is solved, based on the technique for order preference by similarity to ideal solution approach to obtain the compromise route design. Results of the case study confirm that the routes of the proposed model perform better than existing routes in terms of network length and service coverage. Additionally, increasing the number of feeder-bus routes decreases maximum route travel time, increases service coverage, and increases network length. To our knowledge, the proposed model is the first bus route design model in the literature to consider simultaneously various stakeholder needs and support for bus route planners in developing alternatives for further evaluation efficiently and systematically.

Suggested Citation

  • Jen-Jia Lin & Huei-In Wong, 2014. "Optimization of a feeder-bus route design by using a multiobjective programming approach," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(5), pages 430-449, July.
  • Handle: RePEc:taf:transp:v:37:y:2014:i:5:p:430-449
    DOI: 10.1080/03081060.2014.912418
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    Cited by:

    1. Alan T. Murray, 2016. "Maximal Coverage Location Problem," International Regional Science Review, , vol. 39(1), pages 5-27, January.
    2. Min-ho Suh & Minjoong Jeong, 2022. "Development of Bus Routes Reorganization Support Software Using the Naïve Bayes Classification Method," Sustainability, MDPI, vol. 14(8), pages 1-19, April.
    3. Zajac, Sandra & Huber, Sandra, 2021. "Objectives and methods in multi-objective routing problems: a survey and classification scheme," European Journal of Operational Research, Elsevier, vol. 290(1), pages 1-25.
    4. Yi Cao & Dandan Jiang & Shan Wang, 2022. "Optimization for Feeder Bus Route Model Design with Station Transfer," Sustainability, MDPI, vol. 14(5), pages 1-15, February.
    5. 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.
    6. GALARZA MONTENEGRO, Bryan David & SÖRENSEN, Kenneth & VANSTEENWEGEN, Pieter, 2023. "A demand-responsive feeder service with a maximum headway at mandatory stops," Working Papers 2023001, University of Antwerp, Faculty of Business and Economics.

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