Towards bundling minimal trees in polygonal maps

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)

    Abstract

    Minimal trees in polygonal maps aim at minimizing the connectivity in a network while avoiding obstacle collision. Being closely related to the Steiner Tree Problem, yet with a different scope, minimal trees aim at connecting origin-destination pairs, given in a bipartite network, to allow the joint transport of information, goods, resources and people. In this paper, we propose a method to tackle the bundling problem of minimal trees in modular bipartite networks by using a two-layer optimization based on Differential Evolution with a convex representation of coordinates. Our computational experiments in polygonal domains considering both convex and non-convex geometry show the feasibility and the efficiency of the proposed approach.

    Original languageEnglish
    Title of host publicationGECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion
    PublisherAssociation for Computing Machinery, Inc
    Pages1813-1820
    Number of pages8
    ISBN (Electronic)9781450357647
    DOIs
    Publication statusPublished - 2018 Jul 6
    Event2018 Genetic and Evolutionary Computation Conference, GECCO 2018 - Kyoto, Japan
    Duration: 2018 Jul 152018 Jul 19

    Other

    Other2018 Genetic and Evolutionary Computation Conference, GECCO 2018
    CountryJapan
    CityKyoto
    Period18/7/1518/7/19

    Keywords

    • Modular Bipartite Networks
    • Modular Minimal Tree

    ASJC Scopus subject areas

    • Computer Science Applications
    • Software
    • Computational Theory and Mathematics
    • Theoretical Computer Science

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  • Cite this

    Parque Tenorio, V., & Miyashita, T. (2018). Towards bundling minimal trees in polygonal maps. In GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion (pp. 1813-1820). Association for Computing Machinery, Inc. https://doi.org/10.1145/3205651.3208316