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

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  • 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
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    References listed on IDEAS

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    1. Igor Averbakh & Jordi Pereira, 2012. "The flowtime network construction problem," IISE Transactions, Taylor & Francis Journals, vol. 44(8), pages 681-694.
    2. 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.
    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. 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.
    6. 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.
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    Cited by:

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