IDEAS home Printed from https://ideas.repec.org/a/spr/coopap/v63y2016i3p755-792.html
   My bibliography  Save this article

Branch-and-cut-and-price algorithms for the Degree Constrained Minimum Spanning Tree Problem

Author

Listed:
  • Luis Bicalho
  • Alexandre Cunha
  • Abilio Lucena

Abstract

Assume that a connected undirected edge weighted graph G is given. The Degree Constrained Minimum Spanning Tree Problem (DCMSTP) asks for a minimum cost spanning tree of G where vertex degrees do not exceed given pre-defined upper bounds. In this paper, three exact solution algorithms are investigated for the problem. All of them are Branch-and-cut based and rely on the strongest formulation currently available for the problem. Additionally, to speed up the computation of dual bounds, they all use column generation, in one way or another. To test the algorithms, new hard to solve DCMSTP instances are proposed here. These instances, combined with additional ones taken from the literature, are then used in computational experiments. The experiments compare the new algorithms among themselves and also against the best algorithms currently available in the literature. As an outcome of them, one of the new algorithms stands out on top. Copyright Springer Science+Business Media New York 2016

Suggested Citation

  • Luis Bicalho & Alexandre Cunha & Abilio Lucena, 2016. "Branch-and-cut-and-price algorithms for the Degree Constrained Minimum Spanning Tree Problem," Computational Optimization and Applications, Springer, vol. 63(3), pages 755-792, April.
  • Handle: RePEc:spr:coopap:v:63:y:2016:i:3:p:755-792
    DOI: 10.1007/s10589-015-9788-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10589-015-9788-7
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10589-015-9788-7?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. G. Dantzig & R. Fulkerson & S. Johnson, 1954. "Solution of a Large-Scale Traveling-Salesman Problem," Operations Research, INFORMS, vol. 2(4), pages 393-410, November.
    2. de Souza, Mauricio C. & Martins, Pedro, 2008. "Skewed VNS enclosing second order algorithm for the degree constrained minimum spanning tree problem," European Journal of Operational Research, Elsevier, vol. 191(3), pages 677-690, December.
    3. Volgenant, A., 1989. "A Lagrangean approach to the degree-constrained minimum spanning tree problem," European Journal of Operational Research, Elsevier, vol. 39(3), pages 325-331, April.
    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. Claudio Risso & Eduardo Canale, 2022. "Cost Optimized Design for the Local Wind Turbine Grid of an Onshore Wind Farm," Annals of Operations Research, Springer, vol. 316(2), pages 1187-1203, September.
    2. Chagas, Rosklin Juliano & Valle, Cristiano Arbex & da Cunha, Alexandre Salles, 2018. "Exact solution approaches for the Multi-period Degree Constrained Minimum Spanning Tree Problem," European Journal of Operational Research, Elsevier, vol. 271(1), pages 57-71.
    3. Luiz Viana & Manoel Campêlo & Ignasi Sau & Ana Silva, 2021. "A unifying model for locally constrained spanning tree problems," Journal of Combinatorial Optimization, Springer, vol. 42(1), pages 125-150, July.
    4. Alexandre Salles Cunha, 2022. "Improved formulations and branch-and-cut algorithms for the angular constrained minimum spanning tree problem," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 379-413, August.

    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. Lisa K. Fleischer & Adam N. Letchford & Andrea Lodi, 2006. "Polynomial-Time Separation of a Superclass of Simple Comb Inequalities," Mathematics of Operations Research, INFORMS, vol. 31(4), pages 696-713, November.
    2. Fernandes, Lucinda Matos & Gouveia, Luis, 1998. "Minimal spanning trees with a constraint on the number of leaves," European Journal of Operational Research, Elsevier, vol. 104(1), pages 250-261, January.
    3. Bernardino, Raquel & Paias, Ana, 2018. "Solving the family traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 267(2), pages 453-466.
    4. Olcay Polat & Duygu Topaloğlu, 2022. "Collection of different types of milk with multi-tank tankers under uncertainty: a real case study," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 1-33, April.
    5. Rostami, Borzou & Malucelli, Federico & Belotti, Pietro & Gualandi, Stefano, 2016. "Lower bounding procedure for the asymmetric quadratic traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 253(3), pages 584-592.
    6. Neves-Moreira, Fábio & Almada-Lobo, Bernardo & Guimarães, Luís & Amorim, Pedro, 2022. "The multi-product inventory-routing problem with pickups and deliveries: Mitigating fluctuating demand via rolling horizon heuristics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    7. Stock-Williams, Clym & Swamy, Siddharth Krishna, 2019. "Automated daily maintenance planning for offshore wind farms," Renewable Energy, Elsevier, vol. 133(C), pages 1393-1403.
    8. Furini, Fabio & Persiani, Carlo Alfredo & Toth, Paolo, 2016. "The Time Dependent Traveling Salesman Planning Problem in Controlled Airspace," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 38-55.
    9. Shen, Yunzhuang & Sun, Yuan & Li, Xiaodong & Eberhard, Andrew & Ernst, Andreas, 2023. "Adaptive solution prediction for combinatorial optimization," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1392-1408.
    10. Schuijbroek, J. & Hampshire, R.C. & van Hoeve, W.-J., 2017. "Inventory rebalancing and vehicle routing in bike sharing systems," European Journal of Operational Research, Elsevier, vol. 257(3), pages 992-1004.
    11. Almoustafa, Samira & Hanafi, Said & Mladenović, Nenad, 2013. "New exact method for large asymmetric distance-constrained vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 226(3), pages 386-394.
    12. Tang, Lixin & Liu, Jiyin & Rong, Aiying & Yang, Zihou, 2000. "A multiple traveling salesman problem model for hot rolling scheduling in Shanghai Baoshan Iron & Steel Complex," European Journal of Operational Research, Elsevier, vol. 124(2), pages 267-282, July.
    13. Og[breve]uz, Ceyda & Sibel Salman, F. & Bilgintürk YalçIn, Zehra, 2010. "Order acceptance and scheduling decisions in make-to-order systems," International Journal of Production Economics, Elsevier, vol. 125(1), pages 200-211, May.
    14. Wang, Zutong & Guo, Jiansheng & Zheng, Mingfa & Wang, Ying, 2015. "Uncertain multiobjective traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 241(2), pages 478-489.
    15. Zhang, Zijun & Kusiak, Andrew & Song, Zhe, 2013. "Scheduling electric power production at a wind farm," European Journal of Operational Research, Elsevier, vol. 224(1), pages 227-238.
    16. Santos, Lui­s & Coutinho-Rodrigues, João & Current, John R., 2008. "Implementing a multi-vehicle multi-route spatial decision support system for efficient trash collection in Portugal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(6), pages 922-934, July.
    17. Nicolas Jozefowiez & Gilbert Laporte & Frédéric Semet, 2012. "A Generic Branch-and-Cut Algorithm for Multiobjective Optimization Problems: Application to the Multilabel Traveling Salesman Problem," INFORMS Journal on Computing, INFORMS, vol. 24(4), pages 554-564, November.
    18. Rahma Lahyani & Leandro C. Coelho & Jacques Renaud, 2018. "Alternative formulations and improved bounds for the multi-depot fleet size and mix vehicle routing problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 125-157, January.
    19. Anja Fischer & Frank Fischer, 2015. "An extended approach for lifting clique tree inequalities," Journal of Combinatorial Optimization, Springer, vol. 30(3), pages 489-519, October.
    20. Martinhon, Carlos & Lucena, Abilio & Maculan, Nelson, 2004. "Stronger K-tree relaxations for the vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 158(1), pages 56-71, October.

    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:coopap:v:63:y:2016:i:3:p:755-792. 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.