IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v10y2018i3p30-d135904.html
   My bibliography  Save this article

Optimal Design of Demand-Responsive Feeder Transit Services with Passengers’ Multiple Time Windows and Satisfaction

Author

Listed:
  • Bo Sun

    (School of Transportation, Nantong University, Nantong 226019, China
    Nantong Research Institute for Advanced Communication Technologies, Nantong 226019, China
    College of Civil Engineering, Hebei University of Technology, Tianjin 300401, China)

  • Ming Wei

    (School of Transportation, Nantong University, Nantong 226019, China
    Nantong Research Institute for Advanced Communication Technologies, Nantong 226019, China)

  • Senlai Zhu

    (School of Transportation, Nantong University, Nantong 226019, China)

Abstract

This paper presents a mixed-integer linear programming model for demand-responsive feeder transit services to assign vehicles located at different depots to pick up passengers at the demand points and transport them to the rail station. The proposed model features passengers’ one or several preferred time windows for boarding vehicles at the demand point and their expected ride time. Moreover, passenger satisfaction that was related only to expected ride time is fully accounted for in the model. The objective is to simultaneously minimize the operation costs of total mileage and maximize passenger satisfaction. As the problem is an extension of the nondeterministic polynomial problem with integration of the vehicle route problem, this study further develops an improved bat algorithm to yield meta-optimal solutions for the model in a reasonable amount of time. When this was applied to a case study in Nanjing City, China, the mileage and satisfaction of the proposed model were reduced by 1.4 km and increased by 7.1%, respectively, compared with the traditional model. Sensitivity analyses were also performed to investigate the impact of the number of designed bus routes and weights of objective functions on the model performance. Finally, a comparison of Cplex, standard bat algorithm, and group search optimizer is analyzed to verify the validity of the proposed algorithm.

Suggested Citation

  • Bo Sun & Ming Wei & Senlai Zhu, 2018. "Optimal Design of Demand-Responsive Feeder Transit Services with Passengers’ Multiple Time Windows and Satisfaction," Future Internet, MDPI, vol. 10(3), pages 1-15, March.
    • Handle: RePEc:gam:jftint:v:10:y:2018:i:3:p:30-:d:135904
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/10/3/30/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/10/3/30/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alan Lee & Martin Savelsbergh, 2017. "An extended demand responsive connector," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 25-50, March.
    2. Thibaut Vidal & Teodor Gabriel Crainic & Michel Gendreau & Nadia Lahrichi & Walter Rei, 2012. "A Hybrid Genetic Algorithm for Multidepot and Periodic Vehicle Routing Problems," Operations Research, INFORMS, vol. 60(3), pages 611-624, June.
    3. Szeto, W.Y. & Jiang, Y., 2014. "Transit route and frequency design: Bi-level modeling and hybrid artificial bee colony algorithm approach," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 235-263.
    4. Azi, Nabila & Gendreau, Michel & Potvin, Jean-Yves, 2007. "An exact algorithm for a single-vehicle routing problem with time windows and multiple routes," European Journal of Operational Research, Elsevier, vol. 178(3), pages 755-766, May.
    5. Teodor Gabriel Crainic & Federico Malucelli & Maddalena Nonato & François Guertin, 2005. "Meta-Heuristics for a Class of Demand-Responsive Transit Systems," INFORMS Journal on Computing, INFORMS, vol. 17(1), pages 10-24, February.
    6. Azi, Nabila & Gendreau, Michel & Potvin, Jean-Yves, 2010. "An exact algorithm for a vehicle routing problem with time windows and multiple use of vehicles," European Journal of Operational Research, Elsevier, vol. 202(3), pages 756-763, May.
    7. J. Schulze & T. Fahle, 1999. "A parallel algorithm for the vehicle routing problem with time window constraints," Annals of Operations Research, Springer, vol. 86(0), pages 585-607, January.
    8. Gilbert Laporte, 2009. "Fifty Years of Vehicle Routing," Transportation Science, INFORMS, vol. 43(4), pages 408-416, November.
    9. Jean-Yves Potvin & Samy Bengio, 1996. "The Vehicle Routing Problem with Time Windows Part II: Genetic Search," INFORMS Journal on Computing, INFORMS, vol. 8(2), pages 165-172, May.
    10. M. W. P. Savelsbergh & M. Sol, 1995. "The General Pickup and Delivery Problem," Transportation Science, INFORMS, vol. 29(1), pages 17-29, February.
    11. Marshall L. Fisher & Kurt O. Jörnsten & Oli B. G. Madsen, 1997. "Vehicle Routing with Time Windows: Two Optimization Algorithms," Operations Research, INFORMS, vol. 45(3), pages 488-492, June.
    12. Zhenjun Zhu & Xiucheng Guo & Jun Zeng & Shengrui Zhang, 2017. "Route Design Model of Feeder Bus Service for Urban Rail Transit Stations," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-6, January.
    13. Quadrifoglio, Luca & Li, Xiugang, 2009. "A methodology to derive the critical demand density for designing and operating feeder transit services," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 922-935, December.
    14. Jean-Yves Potvin & Tanguy Kervahut & Bruno-Laurent Garcia & Jean-Marc Rousseau, 1996. "The Vehicle Routing Problem with Time Windows Part I: Tabu Search," INFORMS Journal on Computing, INFORMS, vol. 8(2), pages 158-164, May.
    15. Jean-François Cordeau & Gilbert Laporte, 2007. "The dial-a-ride problem: models and algorithms," Annals of Operations Research, Springer, vol. 153(1), pages 29-46, September.
    16. Calvete, Herminia I. & Gale, Carmen & Oliveros, Maria-Jose & Sanchez-Valverde, Belen, 2007. "A goal programming approach to vehicle routing problems with soft time windows," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1720-1733, March.
    17. Hideki Hashimoto & Mutsunori Yagiura & Shinji Imahori & Toshihide Ibaraki, 2013. "Recent progress of local search in handling the time window constraints of the vehicle routing problem," Annals of Operations Research, Springer, vol. 204(1), pages 171-187, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bo Sun & Ming Wei & Chunfeng Yang & Zhihuo Xu & Han Wang, 2018. "Personalised and Coordinated Demand-Responsive Feeder Transit Service Design: A Genetic Algorithms Approach," Future Internet, MDPI, vol. 10(7), pages 1-14, July.
    2. Giovanni Pau & Alessandro Severino & Antonino Canale, 2019. "Special Issue “New Perspectives in Intelligent Transportation Systems and Mobile Communications towards a Smart Cities Context”," Future Internet, MDPI, vol. 11(11), pages 1-3, October.
    3. Bing Zhang & Zhishan Zhong & Xun Zhou & Yongqiang Qu & Fangwei Li, 2023. "Optimization Model and Solution Algorithm for Rural Customized Bus Route Operation under Multiple Constraints," Sustainability, MDPI, vol. 15(5), pages 1-18, February.
    4. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alan Lee & Martin Savelsbergh, 2017. "An extended demand responsive connector," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 25-50, March.
    2. Bo Sun & Ming Wei & Chunfeng Yang & Zhihuo Xu & Han Wang, 2018. "Personalised and Coordinated Demand-Responsive Feeder Transit Service Design: A Genetic Algorithms Approach," Future Internet, MDPI, vol. 10(7), pages 1-14, July.
    3. Bhusiri, Narath & Qureshi, Ali Gul & Taniguchi, Eiichi, 2014. "The trade-off between fixed vehicle costs and time-dependent arrival penalties in a routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 1-22.
    4. Lahyani, Rahma & Khemakhem, Mahdi & Semet, Frédéric, 2015. "Rich vehicle routing problems: From a taxonomy to a definition," European Journal of Operational Research, Elsevier, vol. 241(1), pages 1-14.
    5. Nguyen, Phuong Khanh & Crainic, Teodor Gabriel & Toulouse, Michel, 2013. "A tabu search for Time-dependent Multi-zone Multi-trip Vehicle Routing Problem with Time Windows," European Journal of Operational Research, Elsevier, vol. 231(1), pages 43-56.
    6. Michelle Dunbar & Simon Belieres & Nagesh Shukla & Mehrdad Amirghasemi & Pascal Perez & Nishikant Mishra, 2020. "A genetic column generation algorithm for sustainable spare part delivery: application to the Sydney DropPoint network," Annals of Operations Research, Springer, vol. 290(1), pages 923-941, July.
    7. Derigs, U. & Kaiser, R., 2007. "Applying the attribute based hill climber heuristic to the vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 177(2), pages 719-732, March.
    8. Liu, Fuh-Hwa Franklin & Shen, Sheng-Yuan, 1999. "A route-neighborhood-based metaheuristic for vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 118(3), pages 485-504, November.
    9. Bochra Rabbouch & Foued Saâdaoui & Rafaa Mraihi, 2021. "Efficient implementation of the genetic algorithm to solve rich vehicle routing problems," Operational Research, Springer, vol. 21(3), pages 1763-1791, September.
    10. Luciano Costa & Claudio Contardo & Guy Desaulniers, 2019. "Exact Branch-Price-and-Cut Algorithms for Vehicle Routing," Transportation Science, INFORMS, vol. 53(4), pages 946-985, July.
    11. Dikas, G. & Minis, I., 2014. "Scheduled paratransit transport systems," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 18-34.
    12. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    13. Yu, Yao & Machemehl, Randy B. & Xie, Chi, 2015. "Demand-responsive transit circulator service network design," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 76(C), pages 160-175.
    14. Regnier-Coudert, Olivier & McCall, John & Ayodele, Mayowa & Anderson, Steven, 2016. "Truck and trailer scheduling in a real world, dynamic and heterogeneous context," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 389-408.
    15. Andrew Lim & Xingwen Zhang, 2007. "A Two-Stage Heuristic with Ejection Pools and Generalized Ejection Chains for the Vehicle Routing Problem with Time Windows," INFORMS Journal on Computing, INFORMS, vol. 19(3), pages 443-457, August.
    16. Schneider, Michael & Schwahn, Fabian & Vigo, Daniele, 2017. "Designing granular solution methods for routing problems with time windows," European Journal of Operational Research, Elsevier, vol. 263(2), pages 493-509.
    17. Correia, Gonçalo Homem de Almeida & van Arem, Bart, 2016. "Solving the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP): A model to explore the impacts of self-driving vehicles on urban mobility," Transportation Research Part B: Methodological, Elsevier, vol. 87(C), pages 64-88.
    18. Diego Cattaruzza & Nabil Absi & Dominique Feillet, 2016. "The Multi-Trip Vehicle Routing Problem with Time Windows and Release Dates," Transportation Science, INFORMS, vol. 50(2), pages 676-693, May.
    19. 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.
    20. Baozhen Yao & Qianqian Yan & Mengjie Zhang & Yunong Yang, 2017. "Improved artificial bee colony algorithm for vehicle routing problem with time windows," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-18, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:10:y:2018:i:3:p:30-:d:135904. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.