IDEAS home Printed from https://ideas.repec.org/a/spr/jglopt/v56y2013i3p1073-1100.html
   My bibliography  Save this article

Correlative sparsity structures and semidefinite relaxations for concave cost transportation problems with change of variables

Author

Listed:
  • Tomohiko Mizutani
  • Makoto Yamashita

Abstract

We present a hierarchy of semidefinite programming (SDP) relaxations for solving the concave cost transportation problem (CCTP), which is known to be NP-hard, with p suppliers and q demanders. In particular, we study cases in which the cost function is quadratic or square-root concave. The key idea of our relaxation methods is in the change of variables to CCTPs, and due to this, we can construct SDP relaxations whose matrix variables are of size O((min {p, q}) ω ) in the relaxation order ω. The sequence of optimal values of SDP relaxations converges to the global minimum of the CCTP as the relaxation order ω goes to infinity. Furthermore, the size of the matrix variables can be reduced to O((min {p, q}) ω-1 ), ω ≥ 2 by using Reznick’s theorem. Numerical experiments were conducted to assess the performance of the relaxation methods. Copyright Springer Science+Business Media, LLC. 2013

Suggested Citation

  • Tomohiko Mizutani & Makoto Yamashita, 2013. "Correlative sparsity structures and semidefinite relaxations for concave cost transportation problems with change of variables," Journal of Global Optimization, Springer, vol. 56(3), pages 1073-1100, July.
    • Handle: RePEc:spr:jglopt:v:56:y:2013:i:3:p:1073-1100
    DOI: 10.1007/s10898-012-9924-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10898-012-9924-1
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10898-012-9924-1?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. Alex Fukunaga, 2011. "A branch-and-bound algorithm for hard multiple knapsack problems," Annals of Operations Research, Springer, vol. 184(1), pages 97-119, April.
    2. Gallo, Giorgio & Sandi, Claudio & Sodini, Claudio, 1980. "An algorithm for the min concave cost flow problem," European Journal of Operational Research, Elsevier, vol. 4(4), pages 248-255, April.
    3. Laurent, M., 2009. "Sums of squares, moment matrices and optimization over polynomials," Other publications TiSEM 9fef820b-69d2-43f2-a501-e, Tilburg University, School of Economics and Management.
    4. Larsson, Torbjorn & Migdalas, Athanasios & Ronnqvist, Mikael, 1994. "A Lagrangean heuristic for the capacitated concave minimum cost network flow problem," European Journal of Operational Research, Elsevier, vol. 78(1), pages 116-129, October.
    5. Pisinger, David, 1999. "An exact algorithm for large multiple knapsack problems," European Journal of Operational Research, Elsevier, vol. 114(3), pages 528-541, 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. Sharma, Anuj & Verma, Vanita & Kaur, Prabhjot & Dahiya, Kalpana, 2015. "An iterative algorithm for two level hierarchical time minimization transportation problem," European Journal of Operational Research, Elsevier, vol. 246(3), pages 700-707.
    2. Prabhjot Kaur & Anuj Sharma & Vanita Verma & Kalpana Dahiya, 2022. "An alternate approach to solve two-level hierarchical time minimization transportation problem," 4OR, Springer, vol. 20(1), pages 23-61, March.

    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. Dell’Amico, Mauro & Delorme, Maxence & Iori, Manuel & Martello, Silvano, 2019. "Mathematical models and decomposition methods for the multiple knapsack problem," European Journal of Operational Research, Elsevier, vol. 274(3), pages 886-899.
    2. Lai, Minghui & Cai, Xiaoqiang & Li, Xiang, 2017. "Mechanism design for collaborative production-distribution planning with shipment consolidation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 137-159.
    3. Martello, Silvano & Monaci, Michele, 2020. "Algorithmic approaches to the multiple knapsack assignment problem," Omega, Elsevier, vol. 90(C).
    4. Olivier Lalonde & Jean-François Côté & Bernard Gendron, 2022. "A Branch-and-Price Algorithm for the Multiple Knapsack Problem," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3134-3150, November.
    5. F Altiparmak & I Karaoglan, 2008. "An adaptive tabu-simulated annealing for concave cost transportation problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(3), pages 331-341, March.
    6. Yan, Shangyao & Luo, So-Chang, 1999. "Probabilistic local search algorithms for concave cost transportation network problems," European Journal of Operational Research, Elsevier, vol. 117(3), pages 511-521, September.
    7. Xiao Wang & Xinzhen Zhang & Guangming Zhou, 2020. "SDP relaxation algorithms for $$\mathbf {P}(\mathbf {P}_0)$$P(P0)-tensor detection," Computational Optimization and Applications, Springer, vol. 75(3), pages 739-752, April.
    8. Laurent, Monique & Vargas, Luis Felipe, 2022. "Finite convergence of sum-of-squares hierarchies for the stability number of a graph," Other publications TiSEM 3998b864-7504-4cf4-bc1d-f, Tilburg University, School of Economics and Management.
    9. Polyxeni-Margarita Kleniati & Panos Parpas & Berç Rustem, 2010. "Partitioning procedure for polynomial optimization," Journal of Global Optimization, Springer, vol. 48(4), pages 549-567, December.
    10. Laurent, M. & Rostalski, P., 2012. "The approach of moments for polynomial equations," Other publications TiSEM f08f3cd2-b83e-4bf1-9322-a, Tilburg University, School of Economics and Management.
    11. Jie Wang & Victor Magron, 2021. "Exploiting term sparsity in noncommutative polynomial optimization," Computational Optimization and Applications, Springer, vol. 80(2), pages 483-521, November.
    12. Cortés, Pablo & Muñuzuri, Jesús & Guadix, José & Onieva, Luis, 2013. "Optimal algorithm for the demand routing problem in multicommodity flow distribution networks with diversification constraints and concave costs," International Journal of Production Economics, Elsevier, vol. 146(1), pages 313-324.
    13. Fook Wai Kong & Polyxeni-Margarita Kleniati & Berç Rustem, 2012. "Computation of Correlated Equilibrium with Global-Optimal Expected Social Welfare," Journal of Optimization Theory and Applications, Springer, vol. 153(1), pages 237-261, April.
    14. de Klerk, E. & Laurent, M., 2010. "Error bounds for some semidefinite programming approaches to polynomial minimization on the hypercube," Other publications TiSEM 619d9658-77df-4b5e-9868-0, Tilburg University, School of Economics and Management.
    15. Sandra S. Y. Tan & Antonios Varvitsiotis & Vincent Y. F. Tan, 2021. "Analysis of Optimization Algorithms via Sum-of-Squares," Journal of Optimization Theory and Applications, Springer, vol. 190(1), pages 56-81, July.
    16. Guanglei Wang & Hassan Hijazi, 2018. "Mathematical programming methods for microgrid design and operations: a survey on deterministic and stochastic approaches," Computational Optimization and Applications, Springer, vol. 71(2), pages 553-608, November.
    17. Vincenzo Bonifaci & Tobias Harks & Guido Schäfer, 2010. "Stackelberg Routing in Arbitrary Networks," Mathematics of Operations Research, INFORMS, vol. 35(2), pages 330-346, May.
    18. Ahmadreza Marandi & Joachim Dahl & Etienne Klerk, 2018. "A numerical evaluation of the bounded degree sum-of-squares hierarchy of Lasserre, Toh, and Yang on the pooling problem," Annals of Operations Research, Springer, vol. 265(1), pages 67-92, June.
    19. V. Jeyakumar & J. B. Lasserre & G. Li, 2014. "On Polynomial Optimization Over Non-compact Semi-algebraic Sets," Journal of Optimization Theory and Applications, Springer, vol. 163(3), pages 707-718, December.
    20. Hao Hu & Renata Sotirov, 2021. "The linearization problem of a binary quadratic problem and its applications," Annals of Operations Research, Springer, vol. 307(1), pages 229-249, December.

    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:56:y:2013:i:3:p:1073-1100. 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.