Meta-learning-based system for solving logistic optimization problems

Alan Dávila de León*, Eduardo Lalla-Ruiz, Belén Melián-Batista, J. Marcos Moreno-Vega

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    1 Citation (Scopus)

    Abstract

    The Algorithm Selection Problem seeks to select the most suitable algorithm for a given problem. For solving it, the algorithm selection systems have to face the so-called cold start. It concerns the disadvantage that arises in those cases where the system involved in the selection of the algorithm has not enough information to give an appropriate recommendation. Bearing that in mind, the main goal of this work is two-fold. On the one hand, a novel meta-learning-based approach that allows selecting a suitable algorithm for solving a given logistic problem is proposed. On the other hand, the proposed approach is enabled to work within cold start situations where a tree-structured hierarchy that enables to compare different metric dataset to identify a particular problem or variation is presented.

    Original languageEnglish
    Title of host publicationComputer Aided Systems Theory – EUROCAST 2017
    Subtitle of host publication16th International Conference, Las Palmas de Gran Canaria, Spain, February 19-24, 2017. Revised Selected Papers, Part I
    EditorsRoberto Moreno-Díaz, Franz Pichler, Alexis Quesada-Arencibia
    Place of PublicationCham
    PublisherSpringer
    Pages339-346
    Number of pages8
    ISBN (Electronic)978-3-319-74718-7
    ISBN (Print)978-3-319-74717-0
    DOIs
    Publication statusPublished - 1 Jan 2018
    Event16th International Conference on Computer Aided Systems Theory, EUROCAST 2017 - Las Palmas de Gran Canaria, Spain
    Duration: 19 Feb 201724 Feb 2017
    Conference number: 16
    http://eurocast2017.fulp.ulpgc.es/

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume10671
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference16th International Conference on Computer Aided Systems Theory, EUROCAST 2017
    Abbreviated titleEUROCAST 2017
    CountrySpain
    CityLas Palmas de Gran Canaria
    Period19/02/1724/02/17
    Internet address

    Keywords

    • Logistic problems
    • Meta-heuristics
    • Meta-learning

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