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Telecommunication Link Restoration Planning with Multiple Facility Types

Author

Listed:
  • Anantaram Balakrishnan
  • Thomas Magnanti
  • Joel Sokol
  • Yi Wang

Abstract

To ensure uninterrupted service, telecommunication networks contain excess (spare) capacity for rerouting (restoring) traffic in the event of a link failure. We study the NP-hard capacity planning problem of economically installing spare capacity on a network to permit link restoration of steady-state traffic. We present a planning model that incorporates multiple facility types, and develop optimization-based heuristic solution methods based on solving a linear programming relaxation and minimum cost network flow subproblems. We establish bounds on the performance of the algorithms, and discuss problem instances that nearly achieve these worst-case bounds. In tests on three real-world problems and numerous randomly-generated problems containing up to 50 nodes and 150 edges, the heuristics provide good solutions (often within 0.5% of optimality) to problems with single facility type, in equivalent or less time than methods from the literature. For multi-facility problems, the gap between our heuristic solution values and the linear programming bounds are larger. However, for small graphs, we show that the optimal linear programming value does not provide a tight bound on the optimal integer value, and our heuristic solutions are closer to optimality than implied by the gaps. Copyright Kluwer Academic Publishers 2001

Suggested Citation

  • Anantaram Balakrishnan & Thomas Magnanti & Joel Sokol & Yi Wang, 2001. "Telecommunication Link Restoration Planning with Multiple Facility Types," Annals of Operations Research, Springer, vol. 106(1), pages 127-154, September.
  • Handle: RePEc:spr:annopr:v:106:y:2001:i:1:p:127-154:10.1023/a:1014509708610
    DOI: 10.1023/A:1014509708610
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    Cited by:

    1. J. Cole Smith & Churlzu Lim & Aydın Alptekinoğlu, 2009. "New product introduction against a predator: A bilevel mixed‐integer programming approach," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(8), pages 714-729, December.
    2. Kennington, Jeffery L. & Olinick, Eli V. & Spiride, Gheorghe, 2007. "Basic mathematical programming models for capacity allocation in mesh-based survivable networks," Omega, Elsevier, vol. 35(6), pages 629-644, December.
    3. Emily A Heath & John E Mitchell & Thomas C Sharkey, 2020. "Models for restoration decision making for a supply chain network after a cyber attack," The Journal of Defense Modeling and Simulation, , vol. 17(1), pages 5-19, January.
    4. Yogesh Agarwal, 2013. "Design of Survivable Networks Using Three- and Four-Partition Facets," Operations Research, INFORMS, vol. 61(1), pages 199-213, February.
    5. Timothy Matisziw & Alan Murray & Tony Grubesic, 2010. "Strategic Network Restoration," Networks and Spatial Economics, Springer, vol. 10(3), pages 345-361, September.
    6. Tianyu Wang & Igor Averbakh, 2022. "Network construction/restoration problems: cycles and complexity," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 51-73, August.
    7. Anantaram Balakrishnan & Thomas L. Magnanti & Joel S. Sokol & Yi Wang, 2002. "Spare-Capacity Assignment For Line Restoration Using a Single-Facility Type," Operations Research, INFORMS, vol. 50(4), pages 617-635, August.

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