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    A neural network and heuristics hybrid strategy for job-shop scheduling problem

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    Main article (456.4Kb)
    Date
    1999-06
    Author
    Yang, Shengxiang;
    Wang, Dingwei
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    Abstract
    A new efficient neural network and heuristics hybrid strategy for job-shop scheduling is presented. The neural network has the property of adapting its connection weights and biases of neural units while solving feasible solution. Heuristics are used to accelerate the solving process of neural network and guarantee its convergence, and to obtain non-schedule schedule from solved feasible solution by neural network with orders of operations determined and unchanged. Computer simulations have shown that the proposed hybrid strategy is of high speed and excellent efficiency.
    Description
    The file attached to this record is the author's final peer reviewed version.
    Citation : Yang, S. and Wang, D. (1999) A neural network and heuristics hybrid strategy for job-shop scheduling problem. Journal of Systems Engineering, 14(2), pp.140-144.
    URI
    https://dora.dmu.ac.uk/handle/2086/19616
    Research Institute : Institute of Artificial Intelligence (IAI)
    Peer Reviewed : Yes
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    • School of Computer Science and Informatics [2970]

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