IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v237y2014i2p580-589.html
   My bibliography  Save this article

Flows over time in time-varying networks: Optimality conditions and strong duality

Author

Listed:
  • Koch, Ronald
  • Nasrabadi, Ebrahim

Abstract

There has been much research on network flows over time due to their important role in real world applications. This has led to many results, but the more challenging continuous time model still lacks some of the key concepts and techniques that are the cornerstones of static network flows. The aim of this paper is to advance the state of the art for dynamic network flows by developing the continuous time analogues of the theory for static network flows. Specifically, we make use of ideas from the static case to establish a reduced cost optimality condition, a negative cycle optimality condition, and a strong duality result for a very general class of network flows over time.

Suggested Citation

  • Koch, Ronald & Nasrabadi, Ebrahim, 2014. "Flows over time in time-varying networks: Optimality conditions and strong duality," European Journal of Operational Research, Elsevier, vol. 237(2), pages 580-589.
  • Handle: RePEc:eee:ejores:v:237:y:2014:i:2:p:580-589
    DOI: 10.1016/j.ejor.2014.01.051
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221714000903
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2014.01.051?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. S. Hashemi & Ebrahim Nasrabadi, 2012. "On solving continuous-time dynamic network flows," Journal of Global Optimization, Springer, vol. 53(3), pages 497-524, July.
    2. Cai, X. & Sha, D. & Wong, C. K., 2001. "Time-varying minimum cost flow problems," European Journal of Operational Research, Elsevier, vol. 131(2), pages 352-374, June.
    3. Opasanon, Sathaporn & Miller-Hooks, Elise, 2006. "Multicriteria adaptive paths in stochastic, time-varying networks," European Journal of Operational Research, Elsevier, vol. 173(1), pages 72-91, August.
    4. L. R. Ford & D. R. Fulkerson, 1958. "Constructing Maximal Dynamic Flows from Static Flows," Operations Research, INFORMS, vol. 6(3), pages 419-433, June.
    5. E. J. Anderson & P. Nash & A. B. Philpott, 1982. "A Class of Continuous Network Flow Problems," Mathematics of Operations Research, INFORMS, vol. 7(4), pages 501-514, November.
    6. A. B. Philpott, 1990. "Continuous-Time Flows in Networks," Mathematics of Operations Research, INFORMS, vol. 15(4), pages 640-661, November.
    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. S. Khodayifar & M. A. Raayatpanah & P. M. Pardalos, 2019. "A polynomial time algorithm for the minimum flow problem in time-varying networks," Annals of Operations Research, Springer, vol. 272(1), pages 29-39, January.
    2. Muyldermans, L. & Van Wassenhove, L.N. & Guide, V.D.R., 2019. "Managing high-end ex-demonstration product returns," European Journal of Operational Research, Elsevier, vol. 277(1), pages 195-214.

    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. S. Khodayifar & M. A. Raayatpanah & P. M. Pardalos, 2019. "A polynomial time algorithm for the minimum flow problem in time-varying networks," Annals of Operations Research, Springer, vol. 272(1), pages 29-39, January.
    2. Urmila Pyakurel & Tanka Nath Dhamala, 2017. "Continuous Dynamic Contraflow Approach for Evacuation Planning," Annals of Operations Research, Springer, vol. 253(1), pages 573-598, June.
    3. Ronald Koch & Ebrahim Nasrabadi & Martin Skutella, 2011. "Continuous and discrete flows over time," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 73(3), pages 301-337, June.
    4. S. Hashemi & Ebrahim Nasrabadi, 2012. "On solving continuous-time dynamic network flows," Journal of Global Optimization, Springer, vol. 53(3), pages 497-524, July.
    5. Hong Zheng & Yi-Chang Chiu, 2011. "A Network Flow Algorithm for the Cell-Based Single-Destination System Optimal Dynamic Traffic Assignment Problem," Transportation Science, INFORMS, vol. 45(1), pages 121-137, February.
    6. Bozhenyuk Alexander & Gerasimenko Evgeniya, 2013. "Algorithm for Monitoring Minimum Cost in Fuzzy Dynamic Networks," Information Technology and Management Science, Sciendo, vol. 16(1), pages 53-59, December.
    7. Nazanin Abbasnezhad & Javad Mehri-Takmeh & Javad Vakili, 2020. "The domination over time and its discretisation," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 30(1), pages 5-24.
    8. S Opasanon & E Miller-Hooks, 2009. "The Safest Escape problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1749-1758, December.
    9. Hong Zheng & Yi-Chang Chiu & Pitu B. Mirchandani, 2015. "On the System Optimum Dynamic Traffic Assignment and Earliest Arrival Flow Problems," Transportation Science, INFORMS, vol. 49(1), pages 13-27, February.
    10. Yuya Higashikawa & Naoki Katoh, 2019. "A Survey on Facility Location Problems in Dynamic Flow Networks," The Review of Socionetwork Strategies, Springer, vol. 13(2), pages 163-208, October.
    11. Elisabeth Lübbecke & Marco E. Lübbecke & Rolf H. Möhring, 2019. "Ship Traffic Optimization for the Kiel Canal," Operations Research, INFORMS, vol. 67(3), pages 791-812, May.
    12. de Lima, Vinícius L. & Alves, Cláudio & Clautiaux, François & Iori, Manuel & Valério de Carvalho, José M., 2022. "Arc flow formulations based on dynamic programming: Theoretical foundations and applications," European Journal of Operational Research, Elsevier, vol. 296(1), pages 3-21.
    13. Urmila Pyakurel & Tanka Nath Dhamala & Stephan Dempe, 2017. "Efficient continuous contraflow algorithms for evacuation planning problems," Annals of Operations Research, Springer, vol. 254(1), pages 335-364, July.
    14. Anke Stieber & Armin Fügenschuh, 2022. "Dealing with time in the multiple traveling salespersons problem with moving targets," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(3), pages 991-1017, September.
    15. Huang, He & Gao, Song, 2012. "Optimal paths in dynamic networks with dependent random link travel times," Transportation Research Part B: Methodological, Elsevier, vol. 46(5), pages 579-598.
    16. He Huang & Song Gao, 2018. "Trajectory-Adaptive Routing in Dynamic Networks with Dependent Random Link Travel Times," Transportation Science, INFORMS, vol. 52(1), pages 102-117, January.
    17. Xie, Chi & Travis Waller, S., 2012. "Parametric search and problem decomposition for approximating Pareto-optimal paths," Transportation Research Part B: Methodological, Elsevier, vol. 46(8), pages 1043-1067.
    18. Ichoua, Soumia & Gendreau, Michel & Potvin, Jean-Yves, 2003. "Vehicle dispatching with time-dependent travel times," European Journal of Operational Research, Elsevier, vol. 144(2), pages 379-396, January.
    19. José R. Correa & Andreas S. Schulz & Nicolás E. Stier-Moses, 2007. "Fast, Fair, and Efficient Flows in Networks," Operations Research, INFORMS, vol. 55(2), pages 215-225, April.
    20. Natashia L. Boland & Martin W. P. Savelsbergh, 2019. "Perspectives on integer programming for time-dependent models," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 147-173, July.

    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:ejores:v:237:y:2014:i:2:p:580-589. 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/locate/eor .

    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.