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

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  • 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
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    References listed on IDEAS

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    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.
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    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.

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