A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem

Yailen Martinez Jimenez, Ann Nowe, Suarez Juliett, Bello Rafael

    Onderzoeksoutput: Conference paper

    17 Citaten (Scopus)

    Samenvatting

    In this work we present a Reinforcement Learning approach for the Flexible Job Shop Scheduling problem. The proposed approach
    follows the ideas of the hierarchical approaches and combines learning and optimization in order to achieve better results. Several problem instances were used to test the algorithm and to compare the results with those reported by previous approaches.
    Originele taal-2English
    TitelProc. Fifth International Conference on Learning and Intelligent Optimization (LION5)
    RedacteurenCarlos A. Coello Coello, Xin Yao
    UitgeverijLecture Notes in Computer Science, Springer
    Pagina's253-262
    Aantal pagina's10
    Volume6683
    ISBN van geprinte versie978-3-642-25565-6
    StatusPublished - 2011
    EvenementUnknown -
    Duur: 1 jan 2011 → …

    Publicatie series

    NaamProc. Fifth International Conference on Learning and Intelligent Optimization (LION5)

    Conference

    ConferenceUnknown
    Periode1/01/11 → …

    Bibliografische nota

    Carlos A. Coello Coello, Xin Yao

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