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Neural network approach for the real time control of a FMS

Gang Hao, Jan S. Shang, Luis G. Vargas

    Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

    Abstract

    In this paper, we proposed a three phased model of the FMS control. The first phase is to identify the feasibility of job moves under given system status. The simple Sigma-Pi type of NN model has been adopted in Phase I for feasibility recognition. The second phase applies the Hopfield-Tank model to determine the most appropriate job moves from a feasible job set derived from Phase I. This problem is considered to be very difficult not only because of its NP-complete feature, but also because of the need for quick response under real-time environment. An Hopfield-Tank network with a linear energy function is proposed for Phase II. Phase III devotes to routing decisions for MHS. A heuristic algorithm based on Kohonen's Self-Organizing feature maps is proposed.
    Original languageEnglish
    Title of host publicationProceedings of the Hawaii International Conference on System Sciences
    PublisherIEEE
    Pages641-648
    Volume3
    ISBN (Print)818650702
    Publication statusPublished - 1994
    EventProceedings of the 27th Hawaii International Conference on System Sciences (HICSS-27). Part 4 (of 5) - Wailea, HI, USA
    Duration: 4 Jan 19947 Jan 1994

    Publication series

    Name
    Volume3
    ISSN (Electronic)1060-3425

    Conference

    ConferenceProceedings of the 27th Hawaii International Conference on System Sciences (HICSS-27). Part 4 (of 5)
    CityWailea, HI, USA
    Period4/01/947/01/94

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