IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v54y2003i3d10.1057_palgrave.jors.2601510.html
   My bibliography  Save this article

A genetic algorithm approach on tree-like telecommunication network design problem

Author

Listed:
  • G Zhou

    (Zhejiang University of Technology)

  • M Gen

    (Ashikaga Institute of Technology)

Abstract

In the context of telecommunication networks, the network terminals involve certain constraints that are either related with the performance of the corresponding network or with the availability of some classes of devices. In this paper, we discuss a tree-like telecommunication network design problem with the constraint limiting the number of terminals. First, this problem is formulated as a leaf-constrained minimum spanning tree (lc-MST). Then we develop a tree-based genetic representation to encode the candidate solutions of the lc-MST problem. Compared with the existing heuristic algorithm, the numerical results show the high effectiveness of the proposed GA approach on this problem.

Suggested Citation

  • G Zhou & M Gen, 2003. "A genetic algorithm approach on tree-like telecommunication network design problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(3), pages 248-254, March.
    • Handle: RePEc:pal:jorsoc:v:54:y:2003:i:3:d:10.1057_palgrave.jors.2601510
    DOI: 10.1057/palgrave.jors.2601510
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/palgrave.jors.2601510
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/palgrave.jors.2601510?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. 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.
    2. Zhou, Gengui & Gen, Mitsuo, 1999. "Genetic algorithm approach on multi-criteria minimum spanning tree problem," European Journal of Operational Research, Elsevier, vol. 114(1), pages 141-152, 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. 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.
    2. Gen, Mitsuo & Kumar, Anup & Ryul Kim, Jong, 2005. "Recent network design techniques using evolutionary algorithms," International Journal of Production Economics, Elsevier, vol. 98(2), pages 251-261, November.
    3. Altiparmak, Fulya & Dengiz, Berna, 2009. "A cross entropy approach to design of reliable networks," European Journal of Operational Research, Elsevier, vol. 199(2), pages 542-552, December.
    4. 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.

    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. Cerrone, C. & Cerulli, R. & Raiconi, A., 2014. "Relations, models and a memetic approach for three degree-dependent spanning tree problems," European Journal of Operational Research, Elsevier, vol. 232(3), pages 442-453.
    2. Lacour, Renaud, 2014. "Approches de résolution exacte et approchée en optimisation combinatoire multi-objectif, application au problème de l'arbre couvrant de poids minimal," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/14806 edited by Vanderpooten, Daniel.
    3. Altannar Chinchuluun & Panos Pardalos, 2007. "A survey of recent developments in multiobjective optimization," Annals of Operations Research, Springer, vol. 154(1), pages 29-50, October.
    4. Delorme, Xavier & Gandibleux, Xavier & Degoutin, Fabien, 2010. "Evolutionary, constructive and hybrid procedures for the bi-objective set packing problem," European Journal of Operational Research, Elsevier, vol. 204(2), pages 206-217, July.
    5. Abraham P. Punnen & Ruonan Zhang, 2011. "Quadratic bottleneck problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(2), pages 153-164, March.
    6. Juan Villegas & Fernando Palacios & Andrés Medaglia, 2006. "Solution methods for the bi-objective (cost-coverage) unconstrained facility location problem with an illustrative example," Annals of Operations Research, Springer, vol. 147(1), pages 109-141, October.
    7. Perny, Patrice & Spanjaard, Olivier, 2005. "A preference-based approach to spanning trees and shortest paths problems***," European Journal of Operational Research, Elsevier, vol. 162(3), pages 584-601, May.
    8. Zhou, Gengui & Min, Hokey & Gen, Mitsuo, 2003. "A genetic algorithm approach to the bi-criteria allocation of customers to warehouses," International Journal of Production Economics, Elsevier, vol. 86(1), pages 35-45, October.
    9. Wen, Hao & Sang, Song & Qiu, Chenhui & Du, Xiangrui & Zhu, Xiao & Shi, Qian, 2019. "A new optimization method of wind turbine airfoil performance based on Bessel equation and GABP artificial neural network," Energy, Elsevier, vol. 187(C).
    10. Francis Sourd & Olivier Spanjaard, 2008. "A Multiobjective Branch-and-Bound Framework: Application to the Biobjective Spanning Tree Problem," INFORMS Journal on Computing, INFORMS, vol. 20(3), pages 472-484, August.
    11. Si Chen & Ivana Ljubić & S. Raghavan, 2015. "The Generalized Regenerator Location Problem," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 204-220, May.
    12. Neumann, Frank, 2007. "Expected runtimes of a simple evolutionary algorithm for the multi-objective minimum spanning tree problem," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1620-1629, September.
    13. Abilio Lucena & Nelson Maculan & Luidi Simonetti, 2010. "Reformulations and solution algorithms for the maximum leaf spanning tree problem," Computational Management Science, Springer, vol. 7(3), pages 289-311, July.
    14. Min, Hokey & Jeung Ko, Hyun & Seong Ko, Chang, 2006. "A genetic algorithm approach to developing the multi-echelon reverse logistics network for product returns," Omega, Elsevier, vol. 34(1), pages 56-69, January.
    15. Clímaco, João C.N. & Eugénia Captivo, M. & Pascoal, Marta M.B., 2010. "On the bicriterion - minimal cost/minimal label - spanning tree problem," European Journal of Operational Research, Elsevier, vol. 204(2), pages 199-205, July.
    16. José Arroyo & Pedro Vieira & Dalessandro Vianna, 2008. "A GRASP algorithm for the multi-criteria minimum spanning tree problem," Annals of Operations Research, Springer, vol. 159(1), pages 125-133, March.
    17. Knowles, Joshua D. & Corne, David W., 2002. "Enumeration of Pareto optimal multi-criteria spanning trees - a proof of the incorrectness of Zhou and Gen's proposed algorithm," European Journal of Operational Research, Elsevier, vol. 143(3), pages 543-547, December.
    18. Diabat, Ali & Kannan, Devika & Kaliyan, Mathiyazhagan & Svetinovic, Davor, 2013. "An optimization model for product returns using genetic algorithms and artificial immune system," Resources, Conservation & Recycling, Elsevier, vol. 74(C), pages 156-169.
    19. Mercedes Landete & Alfredo Marín & José Luis Sainz-Pardo, 2017. "Decomposition methods based on articulation vertices for degree-dependent spanning tree problems," Computational Optimization and Applications, Springer, vol. 68(3), pages 749-773, December.
    20. Dali Jiang & Haitao Li & Tinghong Yang & De Li, 2016. "Genetic algorithm for inventory positioning problem with general acyclic supply chain networks," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 10(3), pages 367-384.

    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:pal:jorsoc:v:54:y:2003:i:3:d:10.1057_palgrave.jors.2601510. 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.palgrave-journals.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.