IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v34y2000i4p241-253.html
   My bibliography  Save this article

Shortest paths in traffic-light networks

Author

Listed:
  • Chen, Yen-Liang
  • Yang, Hsu-Hao

Abstract

The time-constrained shortest path problem (TCSPP) is an important generalization of the shortest path problem (SPP) and has attracted widespread research interest in recent years. This paper presents a novel time constraint, called traffic-light constraint, to simulate the operations of traffic-light control encountered in intersections of roads. Basically, the constraint consists of a repeated sequence of time windows. In each window, only the cars in specified routes are allowed to pass through the intersection. In a practical sense, this means that a car needs to wait if the light for its direction is red and can go if it is green. For this kind of network, a shortest path algorithm of time complexity O(r - n3) is developed, where n denotes the number of nodes in the network and r the number of different windows in a node. In addition, we also prove that the time complexity of this algorithm is optimal.

Suggested Citation

  • Chen, Yen-Liang & Yang, Hsu-Hao, 2000. "Shortest paths in traffic-light networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(4), pages 241-253, May.
    • Handle: RePEc:eee:transb:v:34:y:2000:i:4:p:241-253
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191-2615(99)00023-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Julien Bramel & David Simchi-Levi, 1996. "Probabilistic Analyses and Practical Algorithms for the Vehicle Routing Problem with Time Windows," Operations Research, INFORMS, vol. 44(3), pages 501-509, June.
    2. A. W. J. Kolen & A. H. G. Rinnooy Kan & H. W. J. M. Trienekens, 1987. "Vehicle Routing with Time Windows," Operations Research, INFORMS, vol. 35(2), pages 266-273, April.
    3. Robert A. Russell, 1995. "Hybrid Heuristics for the Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 29(2), pages 156-166, May.
    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. Yang, Baiyu & Miller-Hooks, Elise, 2004. "Adaptive routing considering delays due to signal operations," Transportation Research Part B: Methodological, Elsevier, vol. 38(5), pages 385-413, June.
    2. Chen, Yen-Liang & Yang, Hsu-Hao, 2003. "Minimization of travel time and weighted number of stops in a traffic-light network," European Journal of Operational Research, Elsevier, vol. 144(3), pages 565-580, February.
    3. Y-L Chen & L-J Hsiao & K Tang, 2003. "Time analysis for planning a path in a time-window network," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(8), pages 860-870, August.
    4. Qian Ye & Hyun Kim, 2019. "Partial Node Failure in Shortest Path Network Problems," Sustainability, MDPI, vol. 11(22), pages 1-21, November.
    5. Shen, Liang & Shao, Hu & Wu, Ting & Fainman, Emily Zhu & Lam, William H.K., 2020. "Finding the reliable shortest path with correlated link travel times in signalized traffic networks under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).

    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. Zhu, Xiaoyan & Wilhelm, Wilbert E., 2007. "Three-stage approaches for optimizing some variations of the resource constrained shortest-path sub-problem in a column generation context," European Journal of Operational Research, Elsevier, vol. 183(2), pages 564-577, December.
    2. Chen, Yen-Liang & Yang, Hsu-Hao, 2003. "Minimization of travel time and weighted number of stops in a traffic-light network," European Journal of Operational Research, Elsevier, vol. 144(3), pages 565-580, February.
    3. 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.
    4. Diana, Marco & Dessouky, Maged M., 2004. "A new regret insertion heuristic for solving large-scale dial-a-ride problems with time windows," Transportation Research Part B: Methodological, Elsevier, vol. 38(6), pages 539-557, July.
    5. Braysy, Olli & Hasle, Geir & Dullaert, Wout, 2004. "A multi-start local search algorithm for the vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 159(3), pages 586-605, December.
    6. Wanpracha Chaovalitwongse & Dukwon Kim & Panos M. Pardalos, 2003. "GRASP with a New Local Search Scheme for Vehicle Routing Problems with Time Windows," Journal of Combinatorial Optimization, Springer, vol. 7(2), pages 179-207, June.
    7. Li, Haibing & Lim, Andrew, 2003. "Local search with annealing-like restarts to solve the VRPTW," European Journal of Operational Research, Elsevier, vol. 150(1), pages 115-127, October.
    8. Olli Bräysy, 2003. "A Reactive Variable Neighborhood Search for the Vehicle-Routing Problem with Time Windows," INFORMS Journal on Computing, INFORMS, vol. 15(4), pages 347-368, November.
    9. Carrese, Stefano & Cuneo, Valerio & Nigro, Marialisa & Pizzuti, Raffaele & Ardito, Cosimo Federico & Marseglia, Guido, 2022. "Optimization of downstream fuel logistics based on road infrastructure conditions and exposure to accident events," Transport Policy, Elsevier, vol. 124(C), pages 96-105.
    10. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms," Transportation Science, INFORMS, vol. 39(1), pages 104-118, February.
    11. Yi-Kuei Lin & Cheng-Fu Huang & Yi-Chieh Liao, 2019. "Reliability of a stochastic intermodal logistics network under spoilage and time considerations," Annals of Operations Research, Springer, vol. 277(1), pages 95-118, June.
    12. Luca Maria Gambardella & Marco Dorigo, 2000. "An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem," INFORMS Journal on Computing, INFORMS, vol. 12(3), pages 237-255, August.
    13. Jeffrey W. Ohlmann & Michael J. Fry & Barrett W. Thomas, 2008. "Route Design for Lean Production Systems," Transportation Science, INFORMS, vol. 42(3), pages 352-370, August.
    14. 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.
    15. Steven I. Chien * & Zhaoqiong Qin, 2004. "Optimization of bus stop locations for improving transit accessibility," Transportation Planning and Technology, Taylor & Francis Journals, vol. 27(3), pages 211-227, June.
    16. Kafle, Nabin & Zou, Bo & Lin, Jane, 2017. "Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 62-82.
    17. Müller, Juliane, 2010. "Approximative solutions to the bicriterion Vehicle Routing Problem with Time Windows," European Journal of Operational Research, Elsevier, vol. 202(1), pages 223-231, April.
    18. Vis, Iris F.A., 2006. "Survey of research in the design and control of automated guided vehicle systems," European Journal of Operational Research, Elsevier, vol. 170(3), pages 677-709, May.
    19. Belarmino Adenso-Díaz & Mónica González & Emérita García, 1998. "A Hierarchical Approach to Managing Dairy Routing," Interfaces, INFORMS, vol. 28(2), pages 21-31, April.
    20. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.

    More about this item

    Statistics

    Access and download statistics

    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:eee:transb:v:34:y:2000:i:4:p:241-253. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    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.