IDEAS home Printed from https://ideas.repec.org/a/spr/jglopt/v68y2017i3d10.1007_s10898-017-0498-9.html
   My bibliography  Save this article

Approximation guarantees of algorithms for fractional optimization problems arising in dispatching rules for INDS problems

Author

Listed:
  • Hongtan Sun

    (Rensselaer Polytechnic Institute)

  • Thomas C. Sharkey

    (Rensselaer Polytechnic Institute)

Abstract

In this paper, we provide approximation guarantees of algorithms for the fractional optimization problems arising in the dispatching rules from recent literature for Integrated Network Design and Scheduling problems. These fractional optimization problem are proved to be NP-hard. The approximation guarantees are based both on the number of arcs in the network and on the number of machines in the scheduling environment. We further demonstrate, by example, the tightness of the factors for these approximation algorithms.

Suggested Citation

  • Hongtan Sun & Thomas C. Sharkey, 2017. "Approximation guarantees of algorithms for fractional optimization problems arising in dispatching rules for INDS problems," Journal of Global Optimization, Springer, vol. 68(3), pages 623-640, July.
  • Handle: RePEc:spr:jglopt:v:68:y:2017:i:3:d:10.1007_s10898-017-0498-9
    DOI: 10.1007/s10898-017-0498-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10898-017-0498-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10898-017-0498-9?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. Baxter, Matthew & Elgindy, Tarek & Ernst, Andreas T. & Kalinowski, Thomas & Savelsbergh, Martin W.P., 2014. "Incremental network design with shortest paths," European Journal of Operational Research, Elsevier, vol. 238(3), pages 675-684.
    2. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
    3. Kalinowski, Thomas & Matsypura, Dmytro & Savelsbergh, Martin W.P., 2015. "Incremental network design with maximum flows," European Journal of Operational Research, Elsevier, vol. 242(1), pages 51-62.
    4. Nurre, Sarah G. & Cavdaroglu, Burak & Mitchell, John E. & Sharkey, Thomas C. & Wallace, William A., 2012. "Restoring infrastructure systems: An integrated network design and scheduling (INDS) problem," European Journal of Operational Research, Elsevier, vol. 223(3), pages 794-806.
    5. Igor Averbakh & Jordi Pereira, 2012. "The flowtime network construction problem," IISE Transactions, Taylor & Francis Journals, vol. 44(8), pages 681-694.
    6. Oleksii Ursulenko & Sergiy Butenko & Oleg Prokopyev, 2013. "A global optimization algorithm for solving the minimum multiple ratio spanning tree problem," Journal of Global Optimization, Springer, vol. 56(3), pages 1029-1043, July.
    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. Ni, Ni & Howell, Brendan J. & Sharkey, Thomas C., 2018. "Modeling the impact of unmet demand in supply chain resiliency planning," Omega, Elsevier, vol. 81(C), pages 1-16.
    2. Camur, Mustafa C. & Sharkey, Thomas C. & Vogiatzis, Chrysafis, 2023. "The stochastic pseudo-star degree centrality problem," European Journal of Operational Research, Elsevier, vol. 308(2), pages 525-539.

    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. Garay-Sianca, Aniela & Nurre Pinkley, Sarah G., 2021. "Interdependent integrated network design and scheduling problems with movement of machines," European Journal of Operational Research, Elsevier, vol. 289(1), pages 297-327.
    2. Aybike Ulusan & Ozlem Ergun, 2018. "Restoration of services in disrupted infrastructure systems: A network science approach," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-28, February.
    3. Averbakh, Igor & Pereira, Jordi, 2015. "Network construction problems with due dates," European Journal of Operational Research, Elsevier, vol. 244(3), pages 715-729.
    4. Garrett, Richard A. & Sharkey, Thomas C. & Grabowski, Martha & Wallace, William A., 2017. "Dynamic resource allocation to support oil spill response planning for energy exploration in the Arctic," European Journal of Operational Research, Elsevier, vol. 257(1), pages 272-286.
    5. Ni, Ni & Howell, Brendan J. & Sharkey, Thomas C., 2018. "Modeling the impact of unmet demand in supply chain resiliency planning," Omega, Elsevier, vol. 81(C), pages 1-16.
    6. Sharkey, Thomas C. & Cavdaroglu, Burak & Nguyen, Huy & Holman, Jonathan & Mitchell, John E. & Wallace, William A., 2015. "Interdependent network restoration: On the value of information-sharing," European Journal of Operational Research, Elsevier, vol. 244(1), pages 309-321.
    7. Igor Averbakh & Jordi Pereira, 2018. "Lateness Minimization in Pairwise Connectivity Restoration Problems," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 522-538, August.
    8. Iloglu, Suzan & Albert, Laura A., 2018. "An integrated network design and scheduling problem for network recovery and emergency response," Operations Research Perspectives, Elsevier, vol. 5(C), pages 218-231.
    9. Tianyu Wang & Igor Averbakh, 2022. "Network construction/restoration problems: cycles and complexity," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 51-73, August.
    10. Natashia Boland & Thomas Kalinowski & Simranjit Kaur, 2016. "Scheduling arc shut downs in a network to maximize flow over time with a bounded number of jobs per time period," Journal of Combinatorial Optimization, Springer, vol. 32(3), pages 885-905, October.
    11. Canbilen Sütiçen, Tuğçe & Batun, Sakine & Çelik, Melih, 2023. "Integrated reinforcement and repair of interdependent infrastructure networks under disaster-related uncertainties," European Journal of Operational Research, Elsevier, vol. 308(1), pages 369-384.
    12. Melih Çelik & Özlem Ergun & Pınar Keskinocak, 2015. "The Post-Disaster Debris Clearance Problem Under Incomplete Information," Operations Research, INFORMS, vol. 63(1), pages 65-85, February.
    13. Canca, David & Andrade-Pineda, José Luis & De-Los-Santos, Alicia & González-R, Pedro Luis, 2021. "A quantitative approach for the long-term assessment of Railway Rapid Transit network construction or expansion projects," European Journal of Operational Research, Elsevier, vol. 294(2), pages 604-621.
    14. Camilo Gomez & Andrés D. González & Hiba Baroud & Claudia D. Bedoya‐Motta, 2019. "Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery," Risk Analysis, John Wiley & Sons, vol. 39(9), pages 1913-1929, September.
    15. Kalinowski, Thomas & Matsypura, Dmytro & Savelsbergh, Martin W.P., 2015. "Incremental network design with maximum flows," European Journal of Operational Research, Elsevier, vol. 242(1), pages 51-62.
    16. Almoghathawi, Yasser & Barker, Kash & Albert, Laura A., 2019. "Resilience-driven restoration model for interdependent infrastructure networks," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 12-23.
    17. Nihal Berktaş & Bahar Yetiş Kara & Oya Ekin Karaşan, 2016. "Solution methodologies for debris removal in disaster response," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(3), pages 403-445, September.
    18. Rachunok, Benjamin & Nateghi, Roshanak, 2020. "The sensitivity of electric power infrastructure resilience to the spatial distribution of disaster impacts," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    19. Rehak, David & Senovsky, Pavel & Hromada, Martin & Lovecek, Tomas & Novotny, Petr, 2018. "Cascading Impact Assessment in a Critical Infrastructure System," International Journal of Critical Infrastructure Protection, Elsevier, vol. 22(C), pages 125-138.
    20. Chao Fang & Piao Dong & Yi-Ping Fang & Enrico Zio, 2020. "Vulnerability analysis of critical infrastructure under disruptions: An application to China Railway High-speed," Journal of Risk and Reliability, , vol. 234(2), pages 235-245, April.

    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:spr:jglopt:v:68:y:2017:i:3:d:10.1007_s10898-017-0498-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.